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JOSCM - Journal of Operations and Supply Chain Management - n. 02 | Jul/Dec 2016

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JOSCM | Journal of Operations and Supply Chain Management - Volume 9 number 2 - July/December 2016

In this issue of Journal of Operations and Supply Chain Management we present to you five papers that cover different areas of our field. Shashi et al. (2016) explore the key success factors to manage sustainable cold supply chains. Still in the SCM field, Handayati et al. (2016) use agent-based simulation to understand contracting issues. Martins et al. (2016), in their turn, analyze intermodal terminals in Brazil and point interesting ways of improving them, considering shippers’ points of view. Devangan (2016) also explores logistic issues by look for ways to optimize the allocation of warehouses, taking into account production and distribution aspects. Finally, Rajashekharaiah (2016) recoups a recurrent and important theme in the operations management field – the use of six sigma techniques to improve process capability.

For more information on this issue, visit the FGV Library System: http://bit.ly/2livcwo

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JOSCM - Journal of Operations and Supply Chain Management - n. 02 | Jul/Dec 2016

  1. 1. Submitted 09.01.2016. Approved 29.06.2016. Evaluated by double blind review process. THE IDENTIFICATION OF KEY SUCCESS FACTORS IN SUSTAINABLE COLD CHAIN MANAGEMENT: INSIGHTS FROM THE INDIAN FOOD INDUSTRY Shashi PhD Scholar at Punjabi University, School of Management Studies – Patiala – Punjab, India shashikashav37@gmail.com Rajwinder Singh Professor at Punjabi University, School of Management Studies – Patiala – Punjab, India rajwindergheer@gmail.com Amir Shabani PhD Scholar at Vrije Universiteit Amsterdam, Faculty of Economics and Business Administration – Amsterdam, The Netherlands a.shabani@vu.nl ABSTRACT: Supply chain sustainability has emerged as an indispensable research agenda for gov- ernments, industriesand non-governmental organizations. Due to the country’s status as a developing nation, cold supply chain management in India is still in its infancy.Today, due to health consciousness and a greater focus on sustainability, customers are demandingfresh, toxic free, highly eco-friendly food products. However, sustainable cold chains have not yet received sufficientattention throughout the world. Therefore, this paper seeks to address cold chain sustainability issues. After an extensive review of the literature and after discussions with cold chain practitioners, we have formulated ten sustainable cold chain constructs. We have then taken this proposed framework and validated it with an empirical study of the Indian food industry. This study includes several alarming findings. Specifi- cally in India: i) environmental issues and social responsibility are not as important as other supplier selection criteria; ii)social responsibility ranks 18th among 19 food supplier selection criteria; iii) low carbon emissionsareviewed as a less important value added trait in comparison with other traits (this means that in India buyers focus more on individual and immediate benefits rather than longer last- ing advantages); iv) life cycle analyses, renewable energy sources and passive cold chains are the least often implemented cold chain practices; v) the government usually encouragescompanies to adopt and implement sustainability in their operations, but in actual practice, training programs that provide guidance in terms of sustainability are less rigorous in comparison to the actual requirements; but on the bright side; vi) business sustainability builds trust between companies and all of their stakeholders and thus contributes to strong chain relationships. KEYWORDS: Food industry,cold supply chain, sustainability, production, supply chain practices. Volume 9 • Number 2 • July - December 2016 http:///dx.doi/10.12660/joscmv9n2p01-16 1
  2. 2. Shashi, Rajwinder Singh, R., Shabani, A.: The identification of key success factors in sustainable cold chain management: Insights from the Indian food industry ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 9 Number 2 p 01 – 162 1. INTRODUCTION Over the past few years, the practical implementation and study of sustainable supply chain management (SSCM) has been growing rapidly to include ecologi- cal, social and financial benefits (Ageron, Gunasek- aran, & Spalanzani, 2012; Zailani, Jeyaraman, Ven- gadasan, & Premkumar, 2012; Bourlakis, Maglaras, Aktas, & Gallear, 2014). Today, sustainability in sup- ply chains (SC) has become an unavoidable subject (Porter & Kramer, 2006) and plays a critical role in ef- ficient SC execution. It enables companies to achieve a high level of efficiency through optimal resource planning (Rao & Hotl, 2005; Beske, Land, & Seuring, 2014). Globally, however, research on sustainabil- ity in cold chain (CC) management has not received enough attention. Indeed, sustainable cold chain management (SCCM) is a strategic tool for achieving social, ecological and economic goals in managing SC activities that deal with perishable products like medicine, blood, dairy, meat, food, vegetable, mush- room, flower and fruit products, etc., which must be processed, kept, stored and distributed under special time and environmental conditions. One of the important branches of CC deals with the food supply. The food industry is subject to regular changes in customer demand patterns (Aramyan, Kooten, Vorst, &Oude Lansink, 2007; Beske et al., 2014; Bourlakis et al., 2014). However, food CC can be divided into “fresh agricultural products” (e.g. vegetables and fruits) and “processed food prod- ucts” (e.g. convenience food and soft drinks). Gen- erally, SCCM demands practices like environmental friendly packaging, the use of passive CC (using ice and water to maintain the temperature of perishable products), temperature-controlled production, cold logistics systems, the use of recyclable packaging, and the systematic handling of returned orders and proper waste disposal, etc. As a consequence, CC re- quires huge amounts of power to maintain the tem- perature of perishable foodstuffs during warehous- ing, transportation and the retail end, which leads to CC producing one percent of all world carbon emis- sions (Bozorgi, Zabinski, Pazour, &Nazzal, 2015). In addition to this, in many developed and developing nations, firms do not accurately dispose of large quantities of these wastes (Nandy et al., 2015). Food production in India was 264.80 million tons in 2013-14, and this figure declined 3% to 257.07 mil- lion tons in 2014-15. Here it is interesting to note that 30-40% of farm products are spoiled due to a lack of cold storage facilities in India. Moreover,India is currently facing high inflation in terms of food prices (Devi, 2014). Thus, declining production, in- creasing waste, environmental issues, new health problems and a growing population indicate that unfavorable conditions will continue in the near fu- ture. Thus, focusing on SCCM will help to cope with the problems we have discussed above. The main fo- cus of this article will be on studying the following research questions: • What are the reasons behind the adoption of sus- tainable CC practices? • What are the food supplier selection criteria? • What are current sustainability environmental issues? • How does SCCM add value for firms and cus- tomers? • What are the categories of sustainable CC? • What are effective CC practices and the dynamic capabilities needed to attain sustainability? • What are the most effective indicators for mea- suring sustainable CC performance? • What are the major hurdles to,and possible pay- backs from sustainable CC? To the best of the authors’ knowledge, this is the first study to focus on CC sustainability in order to as- sist companies in identifying the key success factors, so that all the economic, environmental and social goals can be satisfied simultaneously. This paper has several distinctive features: • For the first time all factors that are likely to in- fluence the performance of SCCM have been identified. • The most important implemented industrial sus- tainable practices and their benefits for enterpris- es as well as for society are discussed. • A number of promising performance indicators for evaluating SCCM have been identified through co- operation with Indian food industry firms. • This paper will provide firms as well as their stakeholders with a clear understanding of what is important to them and what they need to do. Thus, it will surely improve their competitive- ness in meeting sustainability expectations.
  3. 3. Shashi, Rajwinder Singh, R., Shabani, A.: The identification of key success factors in sustainable cold chain management: Insights from the Indian food industry ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 9 Number 2 p 01 – 163 The ensuing sections discuss the state of the art lit- erature in the relevant fields, proposed approach, and results after implementing it in the context of analyz- ing SCCM. There are 7 main sections. Section 2 is a review of the literature related to SSCM. Section 3 presents our conceptual model of SCCM. We discuss our research methodology and empirical analysis in Sections 4 and 5. Finally, Sections 6 and 7 consist of a discussion of the results and our concluding remarks. 2. LITERATURE REVIEW In this section, we review the SC sustainability lit- erature on in order to identify existing gaps. SC sus- tainability has remained at the top of the research agenda over the past few decades in industry as well as academia. The negative impact of industri- al growth and high resource consumption during the 1970s and 1980s has led to an increased general awareness of SSCM (Barber, 2007). Shashi and Singh (2015) address cold logistics management as an im- portant exercise in food SC, focusing on as it focuses on strategic, transparent integrated cooperation and the attaining of company ecological, social and fi- nancial goals through inter-organizational trade processes.Moreover, Gimenez, Sierra, and Rodon (2012) address CC sustainability as a triple bottom line for stakeholder satisfaction. Sustainability in food CC deals with how organiza- tions may be depleting their resources (Bourlakis et al., 2014). Like other products SC, food chain pro- cessing also generates industrial effluents and other wastes (NCCD, 2012). These wastes are also one of the most pervasive concerns in terms of sustainabil- ity. CC by itself may account for 1% of world car- bon emissions (Bozorgi et al., 2015). Thus, there is a strong need to decrease this carbon emission rateby using macroscopic CC methods (Guo & Shao, 2012). Basically, transportation and distribution cost show the level of competency of a company’s CC logistics operations. It thus indicates the sustainable capacity of companies to reduce their fuel consumption, costs and wastes. Meanwhile, exact route planning can re- duce lead times, food spoilage, fuel costs and carbon emissions (Carter & Dresner, 2001; Bogataj, Bogataj, & Vodopivec, 2005). This implies that CC logistics management can not only help attain environmental sustainability, it can minimize costs. Generally, factors such asthe cross-modal links, in- frastructure networks, the amount and nature of in- vestments, rules, coordination and company visions affect CC sustainability (Subin, 2011). Indeed, appro- priate stockroom location, temperature monitoring and the adequate disposal of hazardous materials add sustainability to business processes. Ma and Wang (2010) discuss the importance of freezing at produc- tion, storage and distribution points. In the same vein, Clark (2007) emphasizes that SSCM requires the implementation of a product-oriented approach and a shift towards more valuable product manufactur- ing that can meet buyer expectations. In addition, all upstream and downstream partners should apply specific sustainability practices during their stages (Hanson, Melnyk, & Calantone, 2004). Today, companies demand more from their vendors to help them attain a competitive position. Better buyer-supplier relationships can foster flexibility, customer responsiveness, green purchasing, qual- ity control, added value, reverse logistics and re- cycling (Vachon & Mao, 2008). Shreay, Chouinard, and McCluskey (2016) address the fact that efforts to improvesustainable practices on the part of sup- pliers can minimize total costs and maximize con- sumer satisfaction.This highlights the importance of strategic supplier development programsin gain- ing competence in sustainability. Hence, appropri- ate supplier selection and evaluation can enhance organizational social responsibility in terms of the environment and society (Vachon & Mao, 2006; An- dersen & Skjoett-Larsen, 2009). Moreover, national and local governments, the World Health Organization and other NGOs have been work- ing to save the environment and protect consumers from food scandals (Gruber & Panasiak, 2011). In do- ing so, many governments have also started providing grants to firms to sustain their sustainability programs. This can help firms and their suppliers mitigate the risk of environmental and political uncertainty (Liu, Ke, Wei, Gu, & Chen, 2010). Besides,using recyclable pack- aging material (Shreay et al., 2016), reducing waste and pollution, and using carbon free energy can improve a company’s image (Beske et al., 2014).It is obvious that there is a vast amount of literature available that deals with SSCM. Nevertheless, most of these studies fail to highlight CC sustainability issues. Hence, this study attempts to fill this gap. 3. A CONCEPTUAL MODEL FOR SUSTAINABLE COLD SUPPLY CHAIN MANAGEMENT Based on the literature discussed above, we have developed a conceptual model for SCCM for this
  4. 4. Shashi, Rajwinder Singh, R., Shabani, A.: The identification of key success factors in sustainable cold chain management: Insights from the Indian food industry ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 9 Number 2 p 01 – 164 study based on Ageron et al. (2012). This article uses tenSCCM constructs, namely: (1) reasons behind the adoption of sustainability, (2) food supplier selec- tion criteria, (3) environmental awareness, (4) add- ing value through sustainable CC, (5) sustainable CC categories, (6) sustainable CC practices, (7) sus- tainable CC dynamic activities, (8) sustainable CC performance indicators, (9) sustainable CC hurdles, and (10) sustainable CC paybacks. 3.1. Reasons/motivations behind the adoption of sustain- ability In business, each and every task has a specific objec- tive. These days, the accelerating rise in world tem- perature, the depletion of available resources, and large quantities of soil, water and air pollution due to increased industrialization and large amounts of food waste are some key concerns that must be controlled within a specific period of time (Doonan, Lanoie, & Laplante, 2005; Papargyropoulou, Colenbrander, Sudmant, Gouldson, & Tin, 2015). Global competi- tion is another factor that has made sustainability more important in securing competitive benefits (Ka- diti, 2013). Moreover, customer expectations, govern- ment initiatives, and pressure from related national/ international food safety bodies and health organiza- tions, as well as financial institutions and NGOs have obliged companies and their chain partners to adopt sustainability in their business operations. As a con- sequence, firm managers are taking sustainability se- riously in terms of their business visions. 3.2. Food supplier selection Suppliers are known as the engine of business. Or- ganizations expecttheir suppliers to adopt sustain- able SC practicesto maximize the firm’s integrity. The incorporation of technology on the part of pri- mary suppliers has a significant impact on organi- zational profitability, and supplier performance also has a profound influence on SC performanceoverall (Ageron et al., 2012; Rezitis & Kalantzi, 2016). Ac- cording to Fritz and Schiefer (2008) and Chapbell, Mhlanga, and Lesschaeve (2016), consumers de- mand fresh, safe and value-added food for consump- tion at reasonable prices, as well as its availability through prompt delivery at locations near them. In this regard, selecting an appropriate food supplier is a major decisionthat involves the consideration of criteria such as product freshness, its commitment to fulfilling orders, cost, quality, prompt delivery, environmental friendly operations, service rates and supplier certifications, etc. Our review of the litera- ture has helped us in this identification of food sup- plier selection criteria (Losito, Visciano, Genualdo, & Cardone, 2011; Palak, Ekşioğlu, & Geunes, 2014; Grimm, Hofstetter, and Sarkis, 2014). 3.3. Environmental awareness Environmental awareness issues revolve around all spheres of life. It is essential that all business part- ners should be more familiar with these issues in order to develop a healthy ecological, economic and social environment. Some of the popular sustain- ability issues are organic production, reductions in resource utilization and waste, and the proper dis- posal of waste, green sourcing, lean processing, re- cyclable packaging and logistics, etc. (Guo, Liang, & Xu, 2008; Gunasekaran & Spalanzani, 2012). 3.4. Value adding factors for Sustainable CC Today, adding value at each stage of CC is a para- mount business objective and is associated with con- sumer buying behavior. Therefore, the development of sustainable food value chains could help firms and their partners increase their profits (Martinez et al., 2006). Moreover, value chainsrequire close collaboration between various stakeholders, name- ly: farmers, agribusinesses, governments and civil society who all add value to agricultural products through sorting, grading, processing, green packag- ing, refining purity and taste, etc. (Shashi & Singh, 2015) In this way, the value added through sustain- ability can be used as a diagnostic tool to manage operations, investments and buying decisions that affect CC performance. 3.5.Sustainable CC categories CC categories are frequently implied by the man- agement of equipment and employees. Making de- cisions relating to partners, learning programs and transportation systems, etc. are critical sustainable CC categories inthe food business. Thus, thecom- panyhas to map out the most promising sustainable CC categories to deal with risks and opportunities. These categories can be classified as: partner devel- opment, partner selection, joint development, tech- nical integration, cold logistics integration (Guo & Shao, 2012), organizational learning, stakeholder management, and innovation and life cycle assess- ment (Bai, Sarkis, Wei, & Koh, 2012). However,the selection of sustainability categories dependsvery
  5. 5. Shashi, Rajwinder Singh, R., Shabani, A.: The identification of key success factors in sustainable cold chain management: Insights from the Indian food industry ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 9 Number 2 p 01 – 165 much on a firm’s size and the availability of its re- sources. It can foster strategic planning pertain- ing to energy, products, transportation and mate- rial management,and can also develop a culture of learning and development throughout the chain. 3.6. Sustainable CC practices Sustainable CC practices are important elements in the food industry. As we discussedabove, SCCM permits organizations to implement practices like green sourcing, green packaging, reprocessing and proper waste dumping (James & James, 2010). It significantly affects sustainable CC performance. Environmental sustainability is not possible without adopting SCCM practices. Moreover, the integra- tion of sustainable practices between upstream and downstream partners can increase the effectiveness of operational performance and resource utilization (Carter & Rogers, 2008). 3.7. Sustainable CC dynamic activities A firm’s dynamic activities help develop, expand or/ and adjust its resources to obtain greater cost-effec- tiveness than its competitors. These organizational activities can comein the form of knowledge assess- ment, knowledge acquisition, ability development, partner development, product development, cold lo- gistics integration and CC relationship management. Reflective control over the whole CC process per- mitsnew resource configurations and makes it pos- sible to adapt to sudden changes. Furthermore, these activities help organizations improve chain traceabil- ity and monitoring to satisfy customer expectations. 3.8. Sustainable CC performance indicators Performance measurements play a vital role in eval- uating firm efficiencies and inefficiencies to make the necessary changes in existing structures (Aramy- an et al., 2007). Therefore the right selection of per- formance indicators is of great importance to SCCM. These performance indicators should include reduc- tions in processing costs, inventory costs, waste rates, energy consumption rates, order return rates and an increase in the use of passive CC, etc. (Guo & Shao, 2012). Agricultural products are produced on a seasonal basis; therefore, food safety and control over the food supply during all chain stages is very important for effective performance management (Martinez, Poole, Skinner, Illes, & Lehota, 2006; Fritz & Schiefer, 2008). We have selected these SCCM per- formance indicators after considering all stages of the food supply, starting with production and end- ing with retail stores. 3.9. Sustainable CC hurdles The hurdles that block the implementation of CC sustainability are different compared to general SC. It is essential to identify these hurdles in order to mitigate their impact on a firm’s overall perfor- mance. Some of the major hurdles that have restrict- ed CC sustainability are inadequate CC infrastruc- ture, uneven installation of CC centers, high energy costs, a lack of CC integration, inefficient processes, a lack of effective environmental measures, a lack of government support and a lack of CC expertise (Subin, 2011; Bozorgi et al., 2015). In this section we will underline the major hurdles to the implementa- tion of CC sustainability in a firm’s operations. 3.10. Sustainable CC paybacks There are a number of paybacks to implementing CC sustainability that occur in different forms. These can be in terms of reducing risks, costs, inventory levels, lead times, waste and adding more value, offering greater flexibility, customer satisfaction, improved quality, brand value, improved working conditions and strong inter-organizational relationships, etc. (Barber, 2007; Pagell, Krause, & Klassen, 2008; Luth­ ra, Kumar, Kumar, & Haleem, 2011). Therefore, it is important for organizations to carefully evaluate CC sustainability paybacks. This will enable organiza- tions to maintain strong positions in relation to their competitors and mitigate the risks associated with political uncertainty. 4. RESEARCH METHODOLOGY At this juncture, after formulating the conceptual model for SCCM, we will shed some light on our research methodology for this study. To address this study, we have formulated a semi- structured questionnaire to answer our research questions through primary data. Here we were in- terested in covering all aspects of SCCM. The whole questionnaire was divided into two parts: organiza- tional characteristics and firm sustainability.Organi- zational characteristics were associatedwiththe firm profilewhile thethefirm’s sustainability was divided into 10 proposed conceptual framework constructs.
  6. 6. Shashi, Rajwinder Singh, R., Shabani, A.: The identification of key success factors in sustainable cold chain management: Insights from the Indian food industry ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 9 Number 2 p 01 – 166 Regarding our questionnaire, we ignored the 5 point Likert scale due to its inability to deal with question sensitiveness (Finstad, 2010). As an alternative, we used two 7-point Likert scales and one rank scale to record feedbacks. The first scale covered the 5 sustainable CC constructs (strongly disagree (1) to strongly agree (7)). The aim of this is to underline the firm’s considerations pertaining to the reasons for adopting CC sustainability, environmental aware- ness, performance measurement indicators, hurdles and paybacks. The second scale covered one con- struct with 19 variables of supplier selection criteria- on the basis of a ranking ((1) most important to (19) least important). The intention behind the measure- ment of this construct was to identify the top priori- ties of companies in terms of upstream integration. The third scale covered 4 constructs, namely: add- ing value through sustainability, CC categories, CC practices and dynamic activities (very low extent (1) to a very high extent (7)). The focus behind this is to identify how companies are working to achieve their sustainability goals. The content validity of the proposed questionnaire was examined by sending it to 14 food CC experts.At this point, the aim was to ascertain that the content of our investigation was measuring what we pro- posed to measure. Experts were then asked to give their suggestions, and using them we refined our questionnaire. Afterwards, improved questionnaire was sent to a pilot study to identify any remaining shortcomings. This pilot survey helped us eliminate a few unimportant variables from the questionnaire. Finally, the full-fledged scale survey was conducted in Indian food industry CC from November 2014 to March 2015. A total of 674 questionnaires were sent through the mail to perishable food product CC practitioners. The list of respondents included CEOs, purchase managers, production managers, quality assurance managers, marketing & sales managers, SC managers, retail managers and others. In total, we received 487 filled out questionnaires in return. We only digitalized 463 out of the 487 re- turned questionnaires in SPSS because of (missing values and zero standard deviations) with 24 ques- tionnaires. Descriptive statistics (means, standard deviations and rankings) were used to answer the research questions. The survey findings indicate that the businesses with the greatest representation (32.81%) were from the food processing area. In addition, SC managers accounted for the largest portion of survey respon- dents, equivalent to 21.02%. Table 1lists the business area and job profile for each of the respondents. Table 1: Digitalized survey profile Business Nature Remarks Respondent Profile Remarks Food processing firms 63 (32.81%) CEO 14 (3.02%) Cold logistics service providers 46 (23.95%) Purchase manager 78 (16.84%) Distribution firms 49 (25.52%) Production manager 65 (14.03%) Retail firms 34 (17.70%) Quality assurance manager 58 (12.52%) Total 192 (100%) Marketing & sales manager 63 (13.60%) Supply chain manager 104 (21.09%) Retail manager 52 (11.23%) Others 29 (6.26%) Total 463 (100%) 5. EMPIRICAL ANALYSIS Sustained practices in CC mostly come from out- side India. The country’s CC segment is highly fragmented and not developed properly to attract a large number of domestic specialists. It is clear that the rate of energy usage by CC technologies directly affects both the feasibility and finances of sustain- ability. Unfortunately, due to the use of obsolete equipment and machinery, CC consumes a high rate of energy in India (KPMG, 2009). Thus, authorities in the agriculture, power, education and food seg- ments must work together to encourage the use of advanced CC technology, modern logistics systems, and the development of CC infrastructure networks
  7. 7. Shashi, Rajwinder Singh, R., Shabani, A.: The identification of key success factors in sustainable cold chain management: Insights from the Indian food industry ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 9 Number 2 p 01 – 167 and expertise. In addition, the government must keep on encouraging more private players to invest in Indian CC in order to bring significant compe- tence in sustainability to the food sector. The results obtained in terms of the reasons and mo- tivations behind applying sustainable practices in Indian CCs are displayed in Table 2. Our findings show government rules and regulations are the main reasons that companies have adopted sustainability in both their own operations and in their supplier’s operations. This indicates that government regu- latory requirements are playing a leading role in protecting the environment and society. Moreover, sustainability is a strategic concern, and without top-management support it is difficult to achieve. Our findings indicate that the vision of top manage- ment frequently incorporates financial, societal and ecological responsibilities in their organizational ac- tions and strategic plans. Sustainability refers to social, economic and eco- logical concerns which advocate a better care of cus- tomer expectations. Green packaging, lower prices, higher quality, lower carbon emissions and prompt delivery, etc. are the key drivers of sustainability. In today’s marketplace, firms that ignore sustainability will be ignored by customers when they make their purchases. Moreover, our analysis emphasizes that both customer expectations and market competitive- ness have significantly encouraged sustainable CC practices. Government ecological initiatives have also had a significant impact on the understanding of sustainability issues. In our list of reasons behind the adoption of sustainability, the role of NGOs re- ceived the lowest ranking, while in many studies, pressure on firms to adopt sustainability is said to be significant. Table 2: Reasons for the adoption of sustainability Reasons for the adoption of sustainability Rank Mean scores Std. deviation Government regulatory requirements 1 6.04 1.312 Top management vision 2 5.83 1.826 Customer expectations 3 5.55 1.041 Market competition 4 5.47 1.405 Government ecological initiatives 5 4.79 1.578 NGOs 6 4.32 1.733 In terms of food supplier selection, accuracy (2.24), quality (2.68), product freshness (3.26), cold ware- houses and vehicles (3.59) and price (4.02) are the most promising variables considered. Likewise the supplier order fulfillment capacity (4.42), quantity and cash discounts (4.84) and service rates (5.10) also significantly affect supplier selection. In addi- tion, these firms also give preference to those suppli- ers who are nearest in terms of geographical location (5.56). This is surely to cut inbound costs, leadtimes and reduce food spoilage during transportation. We also can observe here that credit-based sales (8.22) attract firms to buying material in bulk quan- tity from suppliers. One astonishing result of our findings reveals that despite the remarkable global attention paid to the subject of sustainability (i.e. the simultaneous concentration on social, environ- mental and economic goals), in India, environmen- tal issues (10.13) and social responsibility (11.77) are not as important as other economic supplier selection criteria. In spite of this, environmental is- sues are fortunately more important for firms at the time of supplier selection compared to long-term SC relationships (10.36) and personal relationships (12.49). In Table 3, we display the food supplier se- lection criteria.
  8. 8. Shashi, Rajwinder Singh, R., Shabani, A.: The identification of key success factors in sustainable cold chain management: Insights from the Indian food industry ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 9 Number 2 p 01 – 168 Table 3: Food supplier selection criteria Criteria Rank Mean scores Std. deviation Accuracy 1 2.22 1.072 Quality 2 2.68 1.207 Product freshness 3 3.26 1.495 Cold warehouses and vehicles 4 3.59 1.363 Prices 5 4.02 1.850 Order fulfillment capacity 6 4.42 1.329 Quantity and cash discounts 7 5.10 2.152 Service rates 8 5.12 2.848 Geographical proximity 9 5.56 3.939 Variety 10 6.63 3.683 Delivery style 11 6.87 4.027 Certification 12 7.21 5.514 Credit based sales 13 8.22 5.430 Information sharing ability 14 8.43 5.793 Goodwill 15 9.43 5.461 Environmental issues 16 10.13 5.126 Long-term SC relationships 17 10.36 7.960 Social responsibility 18 11.77 7.633 Personal relationships 19 12.49 6.485 Aspects related to the environmental awareness of sustainability are reported in Table 4. This is very im- portant because it shows how environmental aware- ness helps business by lowering overhead costs, offsetting power usage, reducing the cost of waste removal, as well as boosting, easing and reducing the costs of paperless processes, etc. A company may have the most ambitious environmental policy, but unless it makes all of its stockholders environmentally aware so that they understand the philosophy behind their policy, the goals that the company is aiming for will not be achieved. Our findings indicate that the use of green transportation channels, solar energy and passive CC has not yet received serious attention as expected. This may be happening because less CC expertise is available and the complex designing so- lar energy projects in India. Indeed, stricter ecological policies and regulation, reverse logistics and product lifecycle management have started to receive atten- tion. It is also interesting that Indian firms consider getting ISO 14001 certification and reducing both waste and energy consumption to be promising solu- tions for achieving environmental awareness for sus- tainable CC. Table 4: Major aspects of environmental awareness in sustainability Aspects Rank Mean scores Std. deviation Waste reduction 1 6.19 1.124 ISO 14001 Certification 2 6.12 1.314 Reduction of energy consumption 3 5.93 1.381 Lean management 4 5.83 1.279 Proper waste disposal 5 5.72 1.296
  9. 9. Shashi, Rajwinder Singh, R., Shabani, A.: The identification of key success factors in sustainable cold chain management: Insights from the Indian food industry ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 9 Number 2 p 01 – 169 Recyclable packaging 6 5.43 1.574 Safety and agile health 7 5.30 1.514 Lower levels of greenhouse emissions 8 5.29 1.207 Resource management efficiency 9 5.12 1.337 Adoption of latest technology 10 4.98 1.672 Reverse logistics 11 4.64 1.450 Product life cycle management 12 4.31 1.625 Solar energy utilization 13 3.98 1.067 Use of passive CC 14 3.85 1.463 Green transportation channels 15 3.63 1.853 Moreover, prompt delivery, taste, freshness and proper food labeling are important concerns in terms of VA food traits due to their short shelf life. An unpleasant taste for processed farm products has a detrimental effect on their consumption. A large quantity of perishable products gets spoiled during shipping; hence, packaging and expiration dates can help suppliers handle these products within an ap- propriate timeframe. Furthermore, this helps make buyers aware of this product attribute in terms of consumption and controlling food hazards. In ad- dition, having farm products available during the entire year will provide significant added value for customers. Table 5 lists the results for the value add- ed by sustainable CC construct. Our survey results show that low carbon emis- sions are viewed as providing less added value than other traits. This emphasizes that in India, buyers focus more on their individual and immediate ben- efits such as money savings, quality, taste, labeling, availability and less lead time rather than long last- ing benefits such as a healthy environment. We can see that effectively adding value is good for a firm’s business and that of its partners. Not surprisingly, lower prices are the most important VA factor. Table 5: Value adding factors for Sustainable CC Value Adding Factors for Sustainable CC Rank Mean scores Std. deviation Lower price 1 6.18 1.323 Purity 2 6.17 1.204 Quality 3 6.08 1.135 Organic food 4 5.93 1.436 Fresh food 5 5.86 1.310 Taste 6 5.83 1.438 Prompt delivery 7 5.72 1.183 Less supplier lead time 8 5.69 1.203 Environmentally friendly packaging 9 5.60 1.317 Availability 10 5.59 1.562 Proper Labeling 11 5.56 1.336 Less manufacturer lead time 12 5.24 1.478 Reverse logistics 13 5.13 1.372 Grading 14 4.94 2.583 Sorting 15 4.76 1.610 Low carbon emissions 16 4.41 1.939 Variety 17 4.35 1.717
  10. 10. Shashi, Rajwinder Singh, R., Shabani, A.: The identification of key success factors in sustainable cold chain management: Insights from the Indian food industry ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 9 Number 2 p 01 – 1610 Now we turn to the part of this study that deals with sustainable CC categories. Our results emphasize that risk management and CC integration are almost equally important sustainability categories. Firms have adopted technical integration to gain mutual benefits through combining available technologies. Meanwhile, organizations are giving greater pref- erence to learning from the internal as well as the external business environment to maintain their business competitiveness. Stakeholder management is essential for tackling business uncertainty. Here the innovation category (4.00) is neglected to some extent. Strategic orientationin trade related areas is important in the effective management of the entire SC. Table 6 lists sustainable CC categories in order of their importance. Table 6: Sustainable CC categories Sustainable CC categories Rank Mean scores Std. deviation Risk management 1 5.32 1.287 Cold logistics integration 2 5.25 1.463 Technical integration 3 4.99 1.316 Learning 4 4.81 1.614 Stakeholder management 5 4.65 1.692 Strategic orientation 6 4.47 1.535 Supply chain continuity 7 4.40 1.684 Innovation 8 4.00 1.892 Developing sustainable CC practices is not only critical to business growth, but is also beneficial to future generations. Globalization, climatic change and changes in consumption patterns and in- creased middle class purchasing power have simul- taneously raised the need for improved sustainable CC practices. In this regard, improving ecological standards is viewed as the most important sustain- able CC practice. Reducing energy consumption and waste are also receiving attention from firms. Similarly, reducing hazardous/toxic materials in food products is also viewed as important. We have listed sustainable CC practices in the order of their importance in Table 7: Table 7: Sustainable CC practices Practice Rank Mean scores Std. deviation Significant improvement in fulfillment of ecological standards 1 5.93 1.196 Significant reduction in hazardous/toxic materials 2 5.79 1.298 Achieving waste reduction goals 3 5.78 1.009 Strong relationships with the community 4 5.56 1.211 Use of clean production technology 5 5.47 1.224 Reduction in operational costs 6 5.46 1.467 Physical layout designed to optimize materials and energy 7 5.32 1.365 Reverse logistics 8 5.26 1.972 Recycling 9 5.14 1.643 Purchase of packaging that is of lighter weight 10 5.10 2.115 Purchase of recyclable packaging material 11 5.06 1.631
  11. 11. Shashi, Rajwinder Singh, R., Shabani, A.: The identification of key success factors in sustainable cold chain management: Insights from the Indian food industry ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 9 Number 2 p 01 – 1611 Use of life cycle analysis 12 4.63 1.572 Use of renewable energy sources 13 4.26 1.565 Use of passive CC 14 4.01 1.390 Firms are using regular meetings and large amounts of knowledge sharing as the most implemented dy- namic activities. Similarly, knowledge acquisition and evaluation, licensing and partner based synergies are other important major activities that firms have adopted in their organization to promote sustainabil- ity. At this point, the joint development of products is viewed as the least important dynamic activity. Thus we can conclude that there is a focus on the part of of businesses on their own core competencies. Our analysis reveals that the rest of the sustain- able dynamic activity variables are implemented to a great extent by the firm to develop and maintain sustainability. We can also see that the quality of shared knowledge is more crucial than the transpar- ency of the actions taken. Here in Table 8, then, we list the sustainable CC dynamic activities that assist firms in implementation. Table 8: Sustainable CC dynamic activities Dynamic activity Rank Mean scores Std. deviation Regular meetings 1 6.23 1.177 Knowledge sharing 2 6.15 1.249 Knowledge acquisition and evaluation 3 5.93 1.392 Licensing 4 5.90 1.285 Partner-based synergies 5 5.87 1.363 Transparency 6 5.76 1.668 Partner development programs 7 5.64 1.403 Common IT System 8 5.41 1.574 Partner training 9 5.28 1.780 Joint development of products 10 4.82 1.813 When sustainability is implemented, it needs to be measured in order to make changes in existing pat- terns to accomplish predefined sustainability objec- tives. Hence, CC performance measurement is the most important step towards successful and effec- tive SCCM. As we can see from Table 9, reducing the rate of waste is the most appreciated sustainable CC perfor- mance indicator in terms of helping firms quantify their cash and material savings. Reduced levels of carbon emissions and customer complaints and im- proved customer satisfaction rates are also consid- ered in evaluating CC operations. Since CC requires a large amount of energy sources, the evaluation of reduced energy consumption is also a key indicator to ensuring CC sustainability. Overall, firms con- sider sustainable CC performance indicators to be important,since the score of the least important indi- cator (i.e. reduced maintenance costs) is 5.32. Table 9: Sustainable CC performance indicators Sustainable CC performance indicators Rank Mean scores Std. deviation Reduction in waste rate 1 6.04 1.132 Reduction in customer complaint rate 2 5.98 1.211 Reduction in carbon emission rate 3 5.97 1.186
  12. 12. Shashi, Rajwinder Singh, R., Shabani, A.: The identification of key success factors in sustainable cold chain management: Insights from the Indian food industry ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 9 Number 2 p 01 – 1612 Customer satisfaction rate 4 5.94 1.185 Reduction in overall energy use 5 5.86 1.716 Reduced transportation costs 6 5.79 1.481 Shipping accuracy rate 7 5.76 1.379 Reduction in lead time 8 5.72 1.652 Improved product quality rate 9 5.71 1.307 Increased profits 10 5.69 1.373 Reduction in cooling costs 11 5.64 1.439 Reduced inventory costs 12 5.62 1.377 Staff retention 13 5.62 1.247 Order returns 14 5.56 1.624 Reduced processing costs 15 5.54 1.407 Recycling rate 16 5.40 1.438 Reduced warehousing costs 17 5.35 1.512 Reduced maintenance costs 18 5.32 1.420 A list of hurdles that have stifled sustainability is shown in Table 10. These obstacles to implementing sustainable cold chains in India have been hot topics in discussions about why India has yet to become the “Food Basket of the World.” In India, inadequate CC infrastructure, high investment costs, a lack of CC expertise, high energy costs and the complex- ity of designing ways to reduce the consumption of resources and energy are considered to be the big- gest obstacles which have impeded the adoption of CC sustainability. One interesting finding here is that a lack of government support received a value of 4.38, while a lack of training courses is ranked 15th.This means that the government usually has backed firms in the adoption and implementation of sustainability in their operations, but that training courses to guide this process have not been made a requirement. Moreover, available CC has been installed uneven- ly which shows up in the unavailability of multi- commodity based CC capacity. A report published by the Emerson Group emphasizes that most of the available CC technologies in the country are outdat- ed. Hence, the existing structure requires more CC coordination, ideal arrangements, consistent pro- cesses, specific environmental goals and the latest CC technology. Table 10: Sustainable CC hurdles Sustainable CC hurdles Rank Mean scores Std. deviation Inadequate CC infrastructure 1 6.32 1.134 High investment costs 2 6.30 1.136 Lack of CC expertise 3 6.18 1.092 High energy costs 4 6.14 1.120 Complexity of designing ways to reduce re- source/energy consumption 5 6.01 1.078 High costs of hazardous waste disposal 6 5.98 1.236 Lack of CC integration 7 5.97 1.203 Costs of environment friendly packaging 8 5.96 1.404 Lack of specific environmental goals 9 5.95 2.270
  13. 13. Shashi, Rajwinder Singh, R., Shabani, A.: The identification of key success factors in sustainable cold chain management: Insights from the Indian food industry ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 9 Number 2 p 01 – 1613 Unavailability of CC performance measurements 10 5.89 1.117 Uneven installation of CC centers 11 5.86 1.280 Lack of technology 12 5.81 1.538 Complexity of designing ways to recycle used products 13 5.78 1.248 Inefficient processes 14 5.73 2.437 Lack of training courses 15 5.62 1.381 Lack of awareness about adopting reverse logistics 16 5.42 1.363 Lack of government support 17 4.38 1.136 According to the figures reported in Table 11, the ma- jor paybacks of sustainable CC are goodwill, higher customer satisfaction and less lead time. It also leads to significantly more added value, better quality and reduction in waste. As companies have implemented their sustainability plans, working and living condi- tions have definitely improved. Thus, we can observe that business sustainability builds trust between the government, suppliers, firms and all of the stakehold- ers involved in building strong CC relationships. Table 11: Paybacks of sustainable CC Paybacks of sustainable CC Rank Mean scores Std. deviation Goodwill 1 6.18 1.200 Customer satisfaction 2 6.17 1.199 Less lead time 3 6.08 1.386 Large amount of added value 4 5.93 1.357 Reductions in waste 5 5.88 1.148 Improved quality 6 5.87 1.240 Improved working conditions 7 5.80 1.235 Reductions in stocks 8 5.73 1.356 Flexibility 9 5.63 2.049 Reductions in energy costs 10 5.54 1.121 Strong CC relationships 11 5.54 1.883 Development of trust 12 5.53 1.943 6. DISCUSSION Ten sustainable CC constructs have been used to develop the theoretical model framework for this study. In this study, we have specifically conducted an analysis of the Indian food industry in terms of CC sustainability practices. To test and validate this model framework we have developed a semi-struc- tured questionnaire. Perhaps government regulatory requirements create fear among firms in terms of fulfilling the sustainabil- ity prerequisites. The evasion of these prerequisites creates regulatory problems for profit-oriented or- ganizations that can lead to the cancelling of licenses and cash fines. Nonetheless, there is a strong need to evaluate the regulatory compliance rate in small scale industries. The findings of this study indicate that CC infrastructure is a prime area for improvement. Therefore the government should promote private in- vestment in the CC sector, which would be beneficial for sustainable development. Similarly, government efforts in the domain of emission control technology, awareness and expertise could significantly contrib- ute to attaining sustainability. In addition to this, companies need to set their year- ly sustainability goals, and to accomplish these goals
  14. 14. Shashi, Rajwinder Singh, R., Shabani, A.: The identification of key success factors in sustainable cold chain management: Insights from the Indian food industry ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 9 Number 2 p 01 – 1614 companies they need to be fully integrated with their upstream and downstream partners and also be concerned with their own performance. More emphasis should be placed on waste reduction be- cause it also affects waste disposal costs. Likewise, employee retention and training may enable firms to wield better control over emissions during the production process. Usually authorities do not put much emphasison evaluating the workflow of these business units. Managers frequently are not very dedicated towards their entrepreneurial and social responsibility responsibilities, which leads to apa- thy on the part of middle and lower level workers. Thusapathy of this kind can foretell greater carbon emissions, raw material waste, energy waste and internal conflicts in the future. We deem this to be another interesting finding as no previous work has confirmed the impact of management commitment upon the performance of their subordinates. Indeed, firms are giving more preference to deliver- ing pure, quality products to consumers to make them healthier, but not to reduce carbon emissions. Though product purity and quality have only the positive ef- fects on the firm’s consumers, company negligence towards lowering the rate of carbon emissions has a toxic effect on the health of the entire world. In terms of this serious issue, high customer expectations and social pressures are two important aspects of green consciousness. Normally, a lack of awareness on the part of customers and society tends to diminish vol- untary contributions from NGOs, governments and corporate houses. Hence, regular pressure from so- ciety and customers is needed to maintain company progress in terms of sustainability. The partners of any organization are commonly known as the backbone of a business. If the suppli- ers supply low quality raw materials, then it will directly affect the quality of the finished product and the quality of these finished products will nega- tively affect the company’s brand name in the mar- ket. Similarly, the quality of other supplier services also affecta company’s brand name. Thus, CC sup- pliers and sub-suppliers need to pay more attention to improving the accuracy of product orders, qual- ity, freshness, cold warehouse standards, vehicle sustainability and product pricing. Before selecting suppliers, organizations should be more aware of previous sustainability efforts in order to increase their enterprise’s efficiency in protecting the en- vironment. The use of the latest technology and trained manpower can be a game changer in terms of waste reduction. The reduction of waste maximiz- es the rate of product processing, energy conserva- tion and savings in terms of other necessary inputs. Furthermore, these inputs can be used in the next production batch, which will satisfy sustainability expectations (lowering pollution rates, carbon emis- sions, production lead times and fuel usage, etc.) Partner based synergies and information transpar- ency clarify business objectives and facilitate sus- tainable practices among a firm’s partners. Mutual synergies help firms tackle internal and external business hurdles. Since dissatisfied customers are quick to switch to other brands in today’s market- place, reducing customer complaints and optimal problem solving should be considered prime busi- ness imperatives. Our discussions with those in- volved in CC have revealed that CC lead timesare important and noticeable, because as CC lead times increase, the chances of food spoiling also increase along with fuel consumption and monetary losses. Indian companies do not have specific environmen- tal goals and frequently firms resist implementing sustainable practices. Thus, the absence of specific environment management goals, neglect and an unwillingness to tackle this issue are major hurdles that have hindered firms from reaping the benefits of CC sustainability. Previous studies of sustainability have measured safety and agile health issues. We have included this in our investigation, and our findings indicate deci- sively that this is important in terms of sustainabil- ity. This fact should encourage companies to place a higher priority on the safety and health of their em- ployees, society and other living things. Retaining re- liable, experienced and knowledgeable staff reduces customer dissatisfaction and helps builda healthy working environment. In addition to this, a success- ful partner development program enriches firm com- petenceand helps solvefinancial difficulties. 7. CONCLUDING REMARKS In this study, we have developed and analyzed ten SCCM constructs within the context of CC. For each of these constructs, we have in turn identified the major reasons for adopting sustainability, supplier selection criteria, environmental awareness, sus- tainability practices, value adding factors, as well as sustainable CC performance measures, hurdles and possible paybacks. We have discussed the most important implemented industrial sustainable
  15. 15. Shashi, Rajwinder Singh, R., Shabani, A.: The identification of key success factors in sustainable cold chain management: Insights from the Indian food industry ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 9 Number 2 p 01 – 1615 practices and their benefits for enterprises. This article also highlights the gap between required CC capacity and existing CC capacity in India. This study covers almost every aspect of CC sus- tainability. This study’s results argue that sustain- ability could have a profound impact on CC per- formance. However, consumers are also not very aware of the benefits of low carbon emission levels. Thus, this is hurting the efforts of various levels of government and other environment management authorities. Due to high initial costs, developing re- newable energy source infrastructure and passive CC systems are less preferable choices for the food industry. Moreover, as the survey points out, there is a strong need for close integration to compen- sate for the absence of resources. The government and NGOs will have to work in a unified manner to promote training programs to achieve their sus- tainability objects. These programs could also in- crease the efficiency of operational staff, cut waste and make the economy less dependent on carbon. 7.1 Study limitations and future avenues for research One limitation of this study is that CEOs represent- ed only 3.02% of the responses in our survey. Thus, a greater involvement on the part of the industrial elite would be more helpful and would make future survey findings more interesting. Another possible avenue for future research would be applying the proposed model framework to the pharmaceutical industry to measure its approaches to sustainability. Structural equation modeling (SEM) could be used to test the relationships between the sustainability constructs we have developed. 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  17. 17. Submitted 06.03.2016. Approved 15.09.2016. Evaluated by double blind review process. AN INTEGRATED PRODUCTION, INVENTORY, WAREHOUSE LOCATION AND DISTRIBUTION MODEL Lokendra Kumar Devangan Masters in Industrial and Management Engineering from the Indian Institute of Technology – Kanpur – Uttar Pradesh, India lokendra2910@gmail.com ABSTRACT: This paper proposes an integrated production and distribution planning optimization model for multiple manufacturing locations, producing multiple products with deterministic demand at multiple locations. There are multiple modes of transport from plants to demand locations and warehouses. This study presents a model which allows decision makers to optimize plant production, transport and warehouse location simultaneously to fulfill the demands at customer locations within a multi-plant, multi-product, and multi-route supply chain system when the locations of the plants are already fixed. The proposed model is solved for sample problems and tested using real data from a ce- ment manufacturing company in India. An analysis of the results suggests that this model can be used for various strategic and tactical production and planning decisions. KEYWORDS: Supply chain management, integrated models, logistics, transshipment, warehouse location. Volume 9 • Number 2 • July - December 2016 http:///dx.doi/10.12660/joscmv9n2p17-27 17
  18. 18. Devangan, L. K.: An Integrated Production, Inventory, Warehouse Location and Distribution Model ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 9 Number 2 p 17 – 2718 1. INTRODUCTION Extensive research has been performed to opti- mize production planning, inventory, warehouse location and vehicle routing, which have each been addressed as independent problems by several re- searchers (Fawcett & Magnan, 2002). Ganeshan and Harrison (1995) classify supply chain functions into four categories - location, production, inventory and transportation. The independent modeling of sup- ply chain functions has led to suboptimal solutions. There have generally been tradeoffs between com- putational efforts and optimality. Traditionally, in- dependent optimization modeling of different stag- es of the supply chain has been pursued mainly due to limited computational resources. With recent advances in terms of computational re- sources, studies featuring an integrated approach to modeling supply chain functions have been pro- posed (Erengüç, Simpson, and Vakharia 1999, and Kaur, Kanda, and Deshmukh, 2006). As manufac- turing and economic conditions have become more dynamic, there has been a greater need to study sup- ply chain functions using an integrated approach in terms of global supply chain operations. This ap- proach is based on integrating the decision making related to various functions - location, production, inventory and distribution allocations - into a single optimization problem. The fundamental objective of this integrated approach is to optimize the variables for various functions simultaneously instead of se- quentially as they have been optimized in the past. There are several advantages to integrated model- ing such as reduced storage costs, less time spent on product customization and greater visibility in terms of demand. This paper is organized as follows. The following section presents a brief review of the literature in the area of integrated supply chain optimization. Next section presents the proposed integrated sup- ply chain optimization model in detail. After that, the results for problems of varying sizes including a problem with real data are discussed. The final section presents my conclusions and future av- enues for research. 2. LITERATURE REVIEW From the operational perspective, the issues of pro- duction scheduling, inventory policy and distri- bution routes have been modeled and optimized separately (Fawcett & Magnan, 2002). Reviews of integrated models for production, inventory and distribution problems can be found in Erengüç et al. (1999). Chandra and Fisher (1994) compare the com- putational aspects of solving production and distri- bution problems separately as opposed to using a combined model. Dror and Ball (1987) and Chandra (1993) address the coordination of the inventory and distribution functions. Reviews of previous studies of multi-period international facility supply chain location problems have been provided by Canel and Khumawala (1997). They formulate a mixed- integer programming (MIP) model and solve it us- ing a branch and bound design algorithm to decide where to place manufacturing facilities and how to determine production and shipping levels. Ca- nel and Khumawala (2001) also develop a heuristic procedure for solving this MIP model considering a similar problem. Lei, Liu, Ruszczynski, and Park (2006) use a two-phase method to simultaneously solve the production, inventory, and routing prob- lems. Fumero and Vercellis (1991) use Lagrangian relaxation (LR) to solve an MIP model for the inte- grated multi-period optimization of production and logistics operations. They compare the results pro- duced by modeling separately and in an integrated fashion. To minimize costs in the integrated model, they use Lagrangian relaxation (LR) to permit the separation of the production and logistics functions. In this decoupled approach, the production and lo- gistics problems are solved independently in two different optimization models. Pirkul and Jayara- man (1996) develop a cost minimization problem to model a multi-product, 3-echelon, plant capacity and warehouse location problem. Lagrangian relax- ation (LR) is used to find the lower bound and then a heuristic method is used to solve the problem. Dasci and Verter (2001) consider approximated costs and demand to integrate the production and distribu- tion functions. Closed form solutions are obtained to minimize the fixed costs of facility location, op- erations, and transport costs. Arntzen, Brown, Harrison, and Trafton (1995) use a branch and bound algorithm to solve a global supply chain model at Digital Equipment Corporation for multiple products, facilities, echelons, time periods, and transport modes. They then solve it using branch and bound enumeration. Kumanan, Venkatesan, and Kumar (2007) develop two search techniques to minimize total production and distribution costs in a supply chain network. Camm et al. (1997) inte- grate distribution-location problems and a product sourcing problem as two supply chain problems at
  19. 19. Devangan, L. K.: An Integrated Production, Inventory, Warehouse Location and Distribution Model ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 9 Number 2 p 17 – 2719 Proctor and Gamble. They use a geographical infor- mation system along with integer programming and network optimization models to solve the two sub- problems. Dhaenens-Flipo and Finke (2001) model a network flow problem to minimize the cost of a supply chain within a multi-facility, multi-product and multi-period environment. Sabri and Beamon (2000) model stochastic demand, production and supply lead-times in a multi-objective, multi-prod- uct, and multi-echelon model to address strategic and operational planning. Lodree, Jang, and Klein (2004) propose the integration of customer waiting time with the production and distribution functions in the supply chain to determine the production rate and the sequence of vehicle shipments. Garcia, Sánchez, Guerrero, Calle, and Smith (2004) and Silva et al. (2005) model an integrated optimiza- tion problem for perishable products. Garcia et al. (2004) consider a ready-mix concrete production and distribution problem, in which the selection of orders to be processed by a ready-mix concrete manufac- turing plant has to be made, and orders have to have a fixed due date and need to be delivered directly to the customer site. Silva et al. (2005) also study a pro- duction and distribution problem with ready-mix concrete. Patel, Wei, Dessouky, Hao, and Pasakdee (2009) propose a model to minimize the total cost of distribution, storage, inventory and operations, and the determining of production levels appropriate to customer demand. They solve it using two heuristic methods and are able to provide a solution close to an optimal result which offers significant savings in runtime. Jolayemi (2010) develops two versions of a fully optimized model and a partially optimized model for production-distribution and transporta- tion planning in three stage supply chain scenarios. Rong, Akkerman, and Grunow (2011) propose a mixed integer programming model for the integra- tion of food quality for production and distribution in a food supply chain. They introduce the dynam- ics of food degradation by considering factors like storage temperature and transportation equipment in the proposed model. Larbi, Bekrar, Trentesaux, and Beldjilali (2012) formulate an integrated multi- objective supply chain model for an Algerian com- pany in modular form to minimize the cost and time for quality control. Bashiri, Badri, and Talebi (2012) present a mathematical model addressing strategic and tactical planning in a multi-stage, multi-prod- uct production-distribution supply chain network and solve the optimization problem for illustrative numerical problems. Cóccola, Zamarripa, Méndez, and Espuña (2013) and Tang, Goetschalckx, and Mc- Ginnis (2013) propose an integrated production and distribution supply chain problem as a cost minimi- zation problem applied to the chemical and aircraft manufacturing industries. Yu, Normasari, and Lu- ong (2015) develop a cost minimization problem for small and medium size companies to decide how many plants and distribution centers to open and where to open them for a multi-stage supply chain network. Maleki and Cruz-Machado (2013) present a review of the integrated supply chain model and identify theoretical gaps in the integration model. 3. THE INTEGRATED PRODUCTION AND DIS- TRIBUTION PLANNING MODEL 3.1 Problem statement In this study, we have developed an integrated production and distribution planning (IPDP) op- timization model for a multi-product, multi-plant, multi-location and multi-echelon supply chain en- vironment with multiple transport options includ- ing railways and roads. The manufacturing plants have the capacity to produce any product combina- tion within the company’s portfolio. The production capacity at the plant is shared among all the prod- ucts which means that plants do not possess sepa- rate production lines for each type of product. In the literature, two types of costs are defined for any production plant. First we have fixed costs which include administrative costs and construction costs, etc. Second, we have variable input costs which de- pend on the quantity of the product manufactured. The production costs are made up of labor costs, the costs of procuring raw materials, packaging costs and costs related to the processing of the raw materi- als to produce the finished product. In this study, we assume that the unit production costs and unit pack- aging costs have been computed in such a way that they also account for the associated fixed costs of production and the packaging of the products at the plant. These costs vary from plant to plant due to lo- cal geopolitical and economic reasons. The distances between the manufacturing plants to the customer locations, between the plants to the warehouse, and between the warehouse and the customer locations are assumed to be known. Hence, the unit transport cost between two points is known which varies by the mode of transport. In this study, we assume that railways and roads are two of the types of transport available. Since the transportation capacity by any mode of transport from a plant to a warehouse or a
  20. 20. Devangan, L. K.: An Integrated Production, Inventory, Warehouse Location and Distribution Model ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 9 Number 2 p 17 – 2720 customer location is bounded, we need to consider the type of transport in the optimization model. The warehouse inbound and outbound handling costs are dependent on the mode of transport which also makes this problem interesting. The implied unit sales price and taxes vary at each location. The integrated profit maximization model proposed in this paper has been formulated as a mixed inte- ger programming model which determines how to allocate production and distribution to fulfill de- mand at the customer location. The model also de- termines where to place subcontracted warehouses, and allows the user to decide the status of existing warehouses as to whether they should continue or end their operations. This model integrates the op- timization of production, distribution, transport and warehouse location. The integrated production and distribution planning model is formulated as a mixed integer programming model to optimize pro- duction and distribution allocation within produc- tion constraints, obeying transport capacity and the given demand at various customer locations. 3.2 Assumptions The assumptions for this integrated optimization model are as follows: i. Integrated production and distribution optimi- zation has been developed for a planning hori- zon period, which may be a month for example ii. The variable, production and packaging costs have been computed in such a way that they also account for the associated fixed costs of production and the packaging of the products at the plant. iii. Each plant does not the capacity to produce every type of product. iv. The total production capacity of a plant is shared among all the types of products and each prod- uct has its own limited capacity at each plant. v. There is no inventory stored at the plants. vi. Each plant can handle all types of packaging. vii. The selling price for a product varies from customer to customer depending on what has been negotiated. viii. Tax implications vary by customer location. ix. A less than truckload (LTL) shipment is al- lowed without any penalty. x. Customer demands can be fulfilled by sup- plying products directly from plants or ware- houses. 3.3 The formulation of the model The parameters and decision variables used to for- mulate the model are described below: Decision Variables
  21. 21. Devangan, L. K.: An Integrated Production, Inventory, Warehouse Location and Distribution Model ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 9 Number 2 p 17 – 2721 Parameters The profit maximizing objective function and constraints are expressed below: Maximize Subject to
  22. 22. Devangan, L. K.: An Integrated Production, Inventory, Warehouse Location and Distribution Model ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 9 Number 2 p 17 – 2722 3.4 Model Interpretation Equation (1) expresses the goal of the profit maximi- zation problem which is a function of the revenue from the customers, production costs, packaging costs, transport costs, handling costs at warehous- es, excise duty at retailers, and setup costs or rental costs at warehouses. Equation (2) ensures that the quantity of supply of any product type for any plant, warehouse and customer demand location combi- nation does not exceed the production capacity of this product type at that plant. Equation (3) ensures that the quantity of supply of all type of products for any plant, warehouse and customer demand lo- cation combination does not exceed the production capacity of the plant. Equation (4) ensures that the quantity of supply of a product with a given type of packaging for any plant, warehouse and customer demand location combination does not exceed the packaging type capacity at that plant. Equation (5) ensures that quantity of supply of any product for any plant, warehouse and customer demand loca- tion combination by a given mode of transport does not exceed the transport capacity allocated for that mode of transport. Equation (6) ensures that the quantity of supply of a product type with a given type of packaging for any plant, warehouse and customer demand location combination does not exceed the maximum demand for this product with this given packaging type at that customer demand location. Equation (7) ensures that the total of supply of a product type with a given type of packaging for any plant, warehouse and customer demand loca- tion combination fulfills the minimum supply of the product for the given packaging type as promised for this customer demand location. This ensures the attainment of a minimum service level agreement as signed with the customer. Equation (8) ensures that no inventory is stored at warehouses on a continual basis and warehouses are used as a transshipment point. Equation (9) ensures that decision variable δj = 1 if warehouse wj is used as a transshipment point. 4. IMPLEMENTATION AND ANALYSIS 4.1 Numerical Examples and Illustrations In this subsection, I will discuss the two numeri- cal examples used to illustrate the proposed mod- el. The examples are based on supply chains with three stages consisting of production units, ware- houses and customer demand locations. The model is solved both for two and three product types. A summary of the results obtained for these different problem sizes are shown in Table 4.1 below. Table 1: Problem cases Case # Plant # Ware- house # Trans Mode # Item type # Pack- aging Type # Location # Constraint # Decision Variable # Itera- tion # Ware- house Located 1 2 2 2 2 2 10 104 354 56 0 2 3 5 2 3 2 50 659 4,985 436 4 3 9 318 2 2 4 4,783 16,811 141,068 10312 150
  23. 23. Devangan, L. K.: An Integrated Production, Inventory, Warehouse Location and Distribution Model ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 9 Number 2 p 17 – 2723 From the table it is clear that the integrated production and distribution planning model is able to solve prob- lems of various sizes. Cases 1 and 2 are examples of op- timization problems, whereas Case 3 is a real problem involving a cement manufacturing company. Case 1 optimizes the production and distribution plan for 2 plants with a 10 location supply chain with 2 types of products, 2 types of packaging, and 2 types of transport modes. It takes 56 iterations to produce the optmimum solution. It does not pre- scribe any warehouse as this is a simple supply chain. Case 2 is an illustrative exmple for a rela- tively more complex supply chain. The optimum solution prescribes subcontracting 4 warehouses to fullfill demand. Case 3 involves 9 plants and 4,783 customer demand locations with two products and two modes of transport, and takes 10,312 iterations to produce its optimum solution and ends up rec- ommending the subcontracting of 150 warehouses. So the proposed model recommends warehouses as transhipment points for complex supply chains whereas it does not for a simple supply chain. Case 3 will be discussed in detail in the next subsec- tion. All of the three cases were solved using SAS OR software (SAS Institute Inc. (2011) and the time taken for all of them was less than 2 minutes. OPT- MODEL, an algebraic modeling language, was used by the SAS/OR software to solve the problems. The OPTMODEL procedure allows efficient program- ming of large optimization problems. It uses the branch and cut algorithm to solve the proposed MIP optimization model. 4.2 Case study The proposed model was implemented for a cement manufacturing organization in India which has 9 manufacturing plants spread across the country serving customers all over the country. Production capacity data for each of the plants was collected from the plant operation managers. The transporta- tion cost, transportation capacity and demand data were collected from the supply chain planning man- agers. They also shared the data for minimum sup- ply agreements and the selling price at different cus- tomer locations. This cement manufacturer produces two types of cement called OPC and PPC which are sold in the market with four types of packaging. In an emerging market like India, there are two types of demand for cement: bulk and retail. The cement manufacturing industry serves the demands of dif- ferent geographical locations and has contracts with dealers to serve end customers. Dealers are the cus- tomers of this manufacturing company. They also serve the bulk demands of the construction indus- try. Manufacturing plants are set up near sources of raw materials. The rate of demand is not constant over time in each region as infrastructure construc- tion activities move to different locations over time. The proposed model which integrates production, warehouse location and distribution planning is ideal for scenarios where the rate of demand is not constant in a region. The proposed model allows the manufacturer to set up or subcontract warehouses to act as transshipment points and serve the demands of customers who are located very far away from the manufacturing plants. The model has also integrat- ed the minimum demand fulfillment agreement and does not differentiate between bulk demand and re- tail demand because the model has been formulated as a profit maximization model. How best to configure cement production, distribu- tion and warehouse planning has been solved using real data collected from this manufacturing organiza- tion. There are 4,783 demand locations and 9 cement plants to serve demand. 318 is the number of ware- houses available to be used as transshipment points. Railways and roads are two of the transport modes. In reality every plant is connected to every ware- house and demand location, but transport cost data is not available for some of the routes. In the baseline scenario, the total demand is 781,321 tons and the ob- jective value is 2,861,932,772 INR. 0.02% of demand is not fulfilled due to lack of transportation route data. The total number of iterations required to solve the problem was 10,312 using a four thread 32GB RAM machine. The optimized solution recommends 150 warehouses. The overall utilization rate is 67%, and there are two plants which are highly underutilized (<=30%), and four plants with high utilization (>80%). The results obtained using real data from this manu- facturing company are in sync with the geographical locations of the plant, warehouse and customer lo- cations. The nearer customer locations are supplied directly from the plant, whereas customer locations that are farther away get supplied by the warehous- es. The warehouses are supplied by various plants. The discussion of these results with plant managers also suggests a reduction in the cost components. The results also suggest that the optimal number of warehouses required is substantially smaller than the number of warehouses operating currently.
  24. 24. Devangan, L. K.: An Integrated Production, Inventory, Warehouse Location and Distribution Model ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 9 Number 2 p 17 – 2724 4.3 Sensitivity analysis In a given process, a utilization rate of more than 80% strains the entire process. Table 2 shows the ob- jective value for different levels of demand in pro- portion to baseline demand, and Table 3 shows plant Table 2 Objective value for different levels of demand Iteration %Profit %Demand Overall Plant Utilization # Warehouses .80*Baseline 79.99% 99.980% 53% 147 .90*Baseline 89.93% 99.980% 60% 148 Baseline Demand 100.00% 99.980% 67% 150 1.10*Baseline 109.85% 99.979% 73% 153 1.20*Baseline 119.55% 99.980% 80% 154 1.30*Baseline 128.84% 99.980% 87% 153 utilization at different levels of demand. Approxi- mately 100% of demand is fulfilled in all of the levels considered. Though the overall utilization rate rang- es from 53% to 87%, plant P4 is always 100% utilized for economic reasons, whereas plants P7 and P9 are the least utilized in every case. Table 3 Utilization for different levels of demand Scenario/Plants P1 P2 P3 P4 P5 P6 P7 P8 P9 .80*Baseline 61% 83% 64% 100% 45% 42% 17% 62% 24% .90*Baseline 69% 100% 83% 100% 52% 48% 19% 70% 27% Baseline Demand 83% 100% 100% 100% 60% 53% 21% 80% 30% 1.10*Baseline 100% 100% 100% 100% 89% 59% 24% 92% 33% 1.20*Baseline 100% 100% 100% 100% 100% 77% 34% 100% 43% 1.30*Baseline 100% 100% 100% 100% 100% 99% 47% 100% 48% These observations have been used to create differ- ent scenarios for production capacities which are applicable to the manufacturing industry. Solu- tions to these scenarios are helpful in production planning and affect profitability in different situa- tions. The objective value and utilization of each of the plants in these scenarios are presented in Tables 4 and 5. The production capacity scenarios are dis- cussed below: a. Scenario: All 9 of the plants are operating at 90% of production capacity. This is analogous to the situation that occurs when plants undergo peri- odic maintenance activities. b. Scenario: Plant P7 is closed. The utilization of plant P7 is only 21% for the baseline demand case. Management may want to close this plant. c. Scenario: Plants P7 & P9 are closed. Similar to P7, plant P9 is also highly underutilized. Management may decide to close both of these plants. d. Scenario: Plants P7 & P9 are closed, and plants P2, P3 & P4 are operating at 90% of production capacity. The remaining plants are operating at 100% capacity. This is analogous to the situa- tion that occurs when P7 and P9 are closed and 100% of the utilized plants are available with 90% capacity occurring due to maintenance ac- tivities. e. Scenario: Plant P4 is closed. Plant P4 is the most economical plant, and is 100% utilized even when demand is at 80%. This plant will have to be shut down for maintenance due to a critical breakdown situation. f. Scenario: Plant P4 is closed and plants P1, P2, P3, P5 & P8 are operating at 90% due to mainte- nance activities.
  25. 25. Devangan, L. K.: An Integrated Production, Inventory, Warehouse Location and Distribution Model ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 9 Number 2 p 17 – 2725 Table 4 Utilization for different production capacity Plant Code Baseline Utilization a) Scenario b) Scenario c) Scenario d) Scenario e) Scenario f) Scenario P1 83% 90% 88% 91% 96% 100% 90% P2 100% 90% 100% 100% 90% 100% 90% P3 100% 90% 100% 100% 90% 100% 90% P4 100% 90% 100% 100% 90% P5 60% 84% 60% 75% 100% 100% 90% P6 53% 54% 61% 69% 72% 77% 90% P7 21% 23% 34% 45% P8 80% 84% 80% 81% 85% 100% 90% P9 30% 30% 40% 35% 37% Objective Value 100% 99% 98% 98% 100% 96% 95% Table 5 Objective value for different production capacities Scenarios Objective Value as % of Baseline Objective # Warehouses a) Scenario 98.79% 145 b) Scenario 97.78% 144 c) Scenario 97.63% 143 d) Scenario 99.87% 152 e) Scenario 95.79% 150 f) Scenario 95.07% 150 5. THE OPTMODEL PROCEDURE IN SAS /OR The data manipulation ability of SAS software makes it easy to handle problems of any size. In the implementation of Case 3 in which real data is used, plant managers know that all plants are not connect- ed by usable transportation routes to the destination points (customer locations or warehouses) hence all possible combinations are not present in the data used for transportation costs. Also it is known from the expected demand data that all customer loca- tions will not have demand for all types of products. In such problems the number of constraint and deci- sion variables cannot be correctly enumerated using permutations and combinations. Considering all the combinations in the programming, some of which are infeasible, also reduces its efficiency as it does not add any value to the objective function. These kinds of challenges in real problems can be very eas- ily programmed using SAS OPTMODE to solve in- tegrated optimization problems. The OPTMODEL procedure is discussed briefly in the next subsection. 6. CONCLUSIONS AND FUTURE WORK The model proposed in this study determines the optimal integrated production, warehouse location and distribution planning as part of a profit maximi- zation problem. Other studies in the literature have formulated the integrated optimization problem as a cost minimization problem. The analysis of solu- tions for a large real supply chain problem involv- ing a cement manufacturing company shows that complex supply chains can be modeled and have good performance. This study presents a model that enables decision makers to simultaneously optimize product and customer allocations and warehouse locations within a multi-plant, multi-product and multi-route supply chain system. The various sce- narios discussed in terms of sensitivity analysis are useful in understanding what leverages profitability and redundant production capacity. These scenarios are highly relevant in a manufacturing industry. In the electronics, apparel and food processing indus- tries, where a large variety of products is produced
  26. 26. Devangan, L. K.: An Integrated Production, Inventory, Warehouse Location and Distribution Model ISSN: 1984-3046 • Journal of Operations and Supply Chain Management Volume 9 Number 2 p 17 – 2726 and transported to many market locations, the pro- posed integrated production and distribution plan- ning model is highly relevant. The model is also useful for planning annual maintenance work or temporary plant shutdowns.  In the presented ap- proach demand is deterministic. This can be fore- casted periodically using historical sales data, and then it can be used as input into proposed models of supply chain optimization. Future research deal- ing with stochastic demand and the lead time in the model for perishable items would be useful. The proposed model can also be extended to consider the penalties that result from half truck loads and routing decisions in the integrated model. REFERENCES Arntzen, B. C., Brown, G. G., Harrison, T. P., & Trafton, L. L. (1995). 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