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Grounded on resource-based view and dynamic capability perspectives, this research aims to explore linkages between the firm's big data management activities (BDMA), green manufacturing (GM) practices, and sustainable business performance (SBP). The research model was empirically evaluated using data collected from 248 pharmaceutical manufacturers in India during the COVID-19 pandemic. The analysis was performed using a covariance-based structural equation modeling using AMOS 20. The results indicate that GM activities impact SBP directly. Further results imply the mediating role of GM practices on the relationship between BDMA and SBP. The analysis reveals that senior management's resource commitment in pharmaceutical firms is a moderating mechanism in strengthening the association between BDMA and GM practices. This study is significant as it provides key theoretical and managerial implications for pharmaceutical sectors during emergent situations.

Building a local supply chain requires separating the regions and creating alliances with local partners and customers, resulting in a new business model. In local supply chains, the factory procures material, parts, and preassembled elements from local suppliers and sells the final products to local customers. Three-dimensional printing (3DP) has the potential to enable a more local, globally connected, and efficient supply chain through reduced inventory and transportation costs transforming the make-to-stock to the make-on-demand production cycle. In this study, we use an integrated Interpretive Structural Model and Decision-making Trial and Evaluation Laboratory technique to explore and assess the challenges faced by the 3DP companies to become enabling partners in the localized supply chains. The scope of the study, which was limited to 3DP of medical parts and components, identified that regulatory compliance, stringent quality standards, and lack of design expertise are significant barriers to developing localized three-dimensional printing ecosystems. Furthermore, the study identified immediate support from the local government, the high collaboration between the stakeholders, and the need for change in business approach as the key drivers for developing 3DP-enabled localized supply chain ecosystems.

Agriculture and allied activities hold a key to sustaining all human activities and ensuring a food-secured future. However, significant issues such as the ever-growing population and cut-throat competition for resources pose a continuous threat to the agricultural supply chains, thereby compromising sustainable agricultural development. To overcome the ever-escalating complex challenges in agricultural supply chains and production systems, advancements in precision agriculture, smart farming, and effective supply chain collaboration are critical for addressing agricultural sustainability challenges. This research study examines the direct effects of industry 4.0 technology capabilities (I4TC) and supply chain integration (SCI) on sustainable agricultural supply chain performance (SASCP). The study investigates the direct and indirect impact of I4TC on SASCP with SCI as the mediating variable; moreover, it seeks to validate the direct influence of I4TC on SCI and SASCP. Based on the data collected from 262 food processing organizations in India, the findings highlight noteworthy impacts of I4TC on SASCP and verify the presence of SCI as a partially mediating variable. Furthermore, the findings extend the body of knowledge on I4TC by recognizing I4TC as an enabler of SCI, thereby leading to enhanced SASCP. From the practitioner's perspective, the current study can help food-processing organizations better understand the importance of SCI in ASCs and provide valuable insights for managing ASCs to achieve SASCP.

Blockchain technology (BCT) has emerged as a promising disruptive technology with significant applications in the agri-food supply chain (AFSC). This paper reviews the BCT’s research trends, benefits, challenges, and applications in AFSC through systematic literature network analysis (SLNA). A total of 187 articles were selected through a systematic literature review of different reputed databases, and citation network analysis was carried out using “VoSviewer” software. The information related to annual scientific production, country-specific production, type of article, subject area and the most relevant sources was analysed using “Biblioshinny” software. The outcomes reveal prominent benefits, including traceability and transparency, immutability, trust, and decentralization. On the other hand, policy and regulations, scalability issues, less skilled human resources, high investment, and interoperability hinder blockchain implementation. Smart contracts, cybersecurity, food safety, and public distribution systems are some of the identified applications of blockchain technology, thus enhancing agri-food supply chains. Various blockchain-based frameworks in AFSC are also discussed in this review. This review offers insights into how findings may guide practitioners and researchers in developing appropriate BCT systems for AFSC. It also provides practical implications and future research directions on the theme.

Indian agricultural value chains are marred with a lack of financial inclusion of smallholder farmers, lengthy payout times, poor quality of products, lack of traceability issues, and lack of industrialization in the value chain. Social entrepreneurs have indispensable tools as information and communication technologies are making inroads in rural developing economies. This study studies the impact of technological capabilities on social entrepreneurship for creating sustainable value creation using survey data from 557 respondents associated with farming and allied activities. The results highlight that digital technology capabilities mediate the relationship between social entrepreneurship and sustainable value creation. The findings present essential insights for academia, practitioners, and policymakers to better shape policies and decisions on social entrepreneurship.

Infrastructure digital transformation may create value for logistics enterprises; but its whole process is still full of uncertainties. Prior research focused on smart control in view of the infrastructure and ignored the driving role of digital governance in the process of digital transformation. Here, the authors investigate the relationship between digital adaptive governance and digital transformation, and actively explore the effect of digitalization on service quality improvement in logistics enterprises. The authors take servitization as the moderator to examine the interaction between digital transformation and service quality. Through 227 valid responds of senior executives and workers at the production line from 46 logistics enterprises in China, the authors use partial least squares and hierarchical regression analysis to test the hypotheses empirically. Results suggest that digital adaptive governance, infrastructure digital transformation and servitization have positive influence on service quality. Digital adaptive governance has positive influence on infrastructure digital transformation.

Today, global food systems are highly susceptible to food safety risks, economic shocks, price volatility, and natural disasters and pandemics, such as the novel coronavirus (COVID‐19). This paper draws from research on food and nutritional security, food fraud and associated economic ecosystem, and the disruptions due to COVID‐19 for socio‐economic inequality globally. It is concluded that the safety risks have pushed enforcement of measures to reduce food supplies, adversely impacting food availability. Also, COVID‐19 is likely to raise fleeting food security and nutritional concerns across the globe, resulting in rises in poverty and food fraud, limiting food supply and access. Accelerated investments intended to develop more inclusive, sustainable, and resilient food systems will help shrink the effect of the pandemic and, hence, offer a way to control the foreseen food security crisis and economic growth. COVID‐19 is likely to raise grave concerns for food, nutritional security, and food fraud.Agri‐food has become the priority industry in the wake of the pandemic.Innovations, collaborative, and resilient models will help recover future agri‐food systems.

The present research work deals with the effect of water absorption on mechanical properties of treated and untreated hemp fiber reinforced polyester composites. Untreated, 10% alkali treated and 10% alkali plus 1% silane treated hemp fiber was added (in 5%, 10% and 15%) to polyester matrix and composites were prepared by hand lay-up process. Samples were prepared as per ASTM standards and test were carried out for tensile strength, flexural strength, impact strength and water absorption. There is an increase in the tensile strength with increase in fiber loading for untreated (41%), alkali treated (64%) and alkali plus silane treated (99%) hemp fiber reinforced polyester composite without water absorption. There is an increase in the tensile strength with an increase in fiber loading for alkali plus silane treated (36%) hemp fiber polyester composite with water absorption, however for untreated and alkali treated hemp fiber polyester composite, initially there is a decrease in the tensile strength followed by subsequent increase in it with increase in fiber loading with water absorption. There is an increase in the flexural strength with increase in fiber loading for untreated (86%), alkali treated (83%) and alkali plus silane treated (160%) hemp fiber reinforced polyester composite without water absorption. There is an increase in the flexural strength with an increase in fiber loading for untreated (63%) and alkali plus silane treated (94%) hemp fiber polyester composite with water absorption, however for alkali treated hemp fiber polyester composite, initially there is an increase in the flexural strength followed by subsequent decrease in it with increase in fiber loading with water absorption. There is a significant increase in the impact strength with increase in fiber loading for untreated, alkali treated and alkali plus silane treated hemp fiber reinforced polyester composite with and without water absorption. Increase in water absorption with fiber loading was observed, the rate being minimum for alkali plus silane treated hemp fiber reinforced composites.

Hygiene has been noticed as one of the most effective procedures against COVID-19 cross-transmission, especially hand hygiene and covering the face with the mask. Therefore, this study tried to peek into the people movements and seeks to understand how people are handling their daily use items like fruits and vegetables, how people are managing unavoidable grooming services, how people are disinfecting themselves after coming from outside, and what all hygienic practices they are following during this pandemic. Furthermore, this study attempts to explore ways through which people are disinfecting their houses. At last, the study seeks to explore the knowledge/information people have about Coronavirus. The study collected primary data through a self-administered questionnaire. A quota sampling technique was used to collect the data. Bivariate analysis was carried out to reach the study findings. Based on the findings, it is the need of the hour to disseminate the information on the use of unhealthy disinfectants as they lack the knowledge about the safe use of various types of cleaners and disinfectants. It is also reiterated that there is an urgency to promote further information on risk factors of Coronavirus among people and compulsion to promote healthy hand hygiene and sanitation practices. There is a need to promote information through mass media and other modes of awareness, such as artwork and announcements.

Traditionally measurements of service quality have followed the expectation-disconfirmation approach. Further, previous studies have shown that negative disconfirmation is more influential than positive disconfirmation. In this research, we hypothesized information systems(IS) service quality scales based on the dimensionality of the expectation-disconfirmation (ED) and desire-disconfirmation (DD) approach. Using the SERVQUAL+ instrument and data collected from 321 IS users, we developed ED and DD based IS service quality scales using contemporary methods, such as LISREL-based CFA. We have proposed and empirically validated the following two new IS service quality constructs: Service Adequacy (difference of expected service and perceived service) and Service Superiority (difference of desired service and perceived service). Our results indicate that both measures have shown better predictive power than earlier scales like SERVQUAL+ and the IS ZOT scales. We have outlined several implications of ED and DD scales to practice and research.

The selection of an efficient partner for any organisation improves its overall performance. In the present research for the selection of an efficient, sustainable partner 49 selection criteria were identified through the exhaustive literature review, and by applying the Delphi technique, the evaluation criteria was reduced to 16. Later, analytic hierarchy process (AHP) was employed for calculating the relative weights of the short listing criteria. Then, the technique for order preference by similarity to ideal solution (TOPSIS) methodology was used for ranking the partners. The results of the AHP approach revealed that cost (includes environmental cost)/price (C8), environmental competencies (concern for environment) (C15), and human resource management and human rights issues (C9) are the top three significant selection criteria and the results of TOPSIS highlighted that 'partner B' is the best partner amongst the three identified partners. The developed model is intended to guide the decision and policy makers in identifying the significance or importance of selection criteria, and for formulating the strategies or policies for the selection of efficient partners.

Procurement of raw material plays a very critical role in a supply chain. In the era where organisations are searching for cost saving innovative ideas due to the increasing cost pressures, the procurement function provides an opportunity to these organisations to remain competitive. Procurement of raw materials in a food supply chain has to face the problems like shortage of raw material, quality, lack of continuous supply of seasonal raw material, inadequately trained labour force, costly imported packing material, infrastructure and technological deficiencies. This demands that the food industry needs to manage the risk/cost trade-off without disregarding freshness, sustainability and corporate social responsibility issues. This paper presents a case study of a food processing plant in India manufacturing potato chips, with potato as the main raw material. The objective of this paper is to identify and evaluate the important criteria that are considered while procuring the raw material in a food supply chain. Delphi technique and analytical hierarchical process (AHP) were used for exploring and ranking the criteria. Quality of the raw material, supplying capacity of the supplier-quantity and price were identified as the most important purchasing criteria.

From centuries, man has always learn concern about his protection which then lead to number developments in every field with regards to textiles. The protective textile is assigned to cover aspect of safety and security of human being in respect. A mosquito repellent fabric is one such product. It protect the human being from the bite mosquito and thereby promising safety from diseases like Malaria, Dengue, Fever etc. which are major concern today. There have been lot of research mosquito repellent textile until now. Synthetic repellent are used for application on the fabric. The major problem faced with them use of natural repellent was its low durability Hence here in the project, we developed mosquito repellent fabrics by treating them with natural oil like Tulsi, lemongrass and Rose mary Keeping in mind the ecological and economical aspect. The application of repellents is done by using the technique of resin finishing. We compared the performance of these fabrics with the performance of synthetic repellent. According to result, the performance of natural oil (especially Lemongrass) was not only at par with the synthetic repellent but also it provides many medicinal advantages as against the toxicity of synthetic repellent. The durability of the Lemongrass oil was comparable with the synthetic [1,21. [ABSTRACT FROM AUTHOR]

Today with business globalisation, the use of third-party logistics service providers (3PLSPs) is becoming prevalent. With the worldwide increasing use of 3PL services, the need for carefully evaluating and selecting the best 3PL is becoming much more critical. Supply chain managers always face the dilemma of selecting the right 3PL. The current study presents an efficient data envelopment analysis (DEA) and analytic hierarchy process (AHP)-based decision framework for 3PL evaluation and selection for an outsourcing arrangement. The analysis results demonstrate the effectiveness of the integrated DEA-AHP model as a simple and flexible decision analysis tool for 3PL evaluation and selection. Further, the application of decision framework has been demonstrated with a real case situation. Finally, the study discusses the implications of the results in a real-life context and concludes with the managerial insights identifying a few inherent limitations of the approach utilised.

The mechanisms of supply chains are omnipresent, but procurement-centric supply-chain management has received little attention in the construction industry, despite its economic weight. A procurement-centric construction supply chain requires client integration and contractor integration to cope with the project complexity and project uncertainty. In this regard, procurement-led supply-chain initiatives using mediated power and non-mediated power of the client organisation can influence contractor integration and project performance. A structural equation model consisting of two exogenous variables - mediated power and non-mediated power of client - and three endogenous variables - client integration, contractor integration and project performance - is developed based on theoretical support. The data are collected from 244 construction professionals working in a variety of construction projects across India. The result of the study suggests that, the use of mediated power by the client organisation accompanied by the involvement of the client in the project relates to the improving of project performance.

SMEs play a very vital role in each market by significantly contributing to each country's gross domestic product (GDP) and labour market. Therefore, proposing new strategies or developing new systems that can help SMEs become more efficient and productive is not only beneficial for SMEs but also for the economy of a country as a whole. The decision about cloud computing adoption is crucial for every manufacturing firm. However, the selection on an appropriate system may prove difficult, especially for small and medium manufacturing enterprises which may not have sufficient economic and human resources to properly implement the system. The present study aims to provide a systematic approach towards the cloud computing adoption. It is worth noting to determine the decisive factors in adoption of cloud computing adoption and to weight them. In this paper, analytic hierarchy process (AHP) is applied to find the importance degree of each criterion and as the measurable indices of the cloud computing adoption. This study considers nine criteria with 51 sub-criteria, which has somewhat already been used, and establishes a ranking model that provides decision makers to assess the factors prior the adoption of cloud computing.

Today third party logistics (3PL) service providers are into almost all the businesses right from providing raw material to packaging. 3PLs are also getting involved in customers concerned with operations. At a suitable price and consideration of all affecting criteria, anything can be outsourced. Any exporter needs to find a smart balance of what to perform in-house and what to hire outside providers to do (i.e., increase verticals and reduce horizontal supply chain operations). Thus, the demand of 3PL provider has become an important issue for organisations seeking quality customer service and cost reduction. The current research presents an integrated data envelopment analysis (DEA) and artificial neural networks (ANN) methodology for the evaluation and selection of 3PL providers. DEA is employed to identify the maximally efficient 3PL and to eliminate the unsuitable ones; and, ANN to rank and make the final selection. The proposed method enables decision makers to better understand the complete evaluation and selection process of 3PL selection. Furthermore, this approach provides a more accurate, effective, and systematic decision support tool for 3PL selection. Finally, an actual industrial application is presented to demonstrate the proposed method.

The Job shop scheduling problem is an important concern in the manufacturing systems. In this paper, the authors have proposed a hybrid firefly algorithm-tabu search combination technique to solve the Job shop scheduling problems. In the proposed algorithm, a complete scheme of algorithm for Job shop scheduling problems is designed and tabu search algorithm is incorporated with the aim of searching for local optimum of each individual. In order to improve the quality of solutions, in each step of the hybrid algorithms, an effective heuristic is proposed. The proposed heuristic reduces the overtime costs of operations by efficient use of the operation's slack. The performance of the proposed algorithm is tested and evaluated solving well-known benchmarked problems. Finally, the computational results are provided for evaluating the performance and effectiveness of the proposed solution approaches. The results have proved the superiority of proposed approach to other methods such as particle swarm optimization, genetic algorithm in terms of both efficiency and success rate.

Landfill site selection is a complex process, which requires the evaluation of multiple criteria. Decision-makers often face difficulties in taking the right decision in a multiple attribute environment. In this paper, an integrated fuzzy-analytical hierarchy process (AHP)–the technique for order preference by similarity to ideal solution (TOPSIS)-based methodology was applied to the municipal solid waste (MSW) landfill site selection problem. To demonstrate the approach taken, a real case of Mumbai city is taken. The model was developed to suit the socio-economic and regulatory set-up. The fuzzy-analytic hierarchy process was used to make pairwise comparisons of criteria to assign weights and rank them, while F-TOPSIS was employed to rank the alternatives. It was found that the fuzzy-AHP–TOPSIS-based methodology can be a powerful guiding tool for MSW management planners. With this modeling approach, the accuracy of landfill site selection procedure can be significantly enhanced as compared to the traditional methods, thereby reducing the cost and time required. The developed methodology helps in representing and analyzing the uncertainty and error in the decision making process of landfill site selection.

Landfill site selection is a complex multi-criteria and time consuming process. The present study aims to identify, evaluate, and prioritize the landfill site selection criteria and finally study the relationship between them, and the degree to which they affect or are affected by one another. In the first stage, experts’ opinion was sought to select the relevant criteria and fuzzy Delphi Method (FDM) was employed to obtain the critical factors for selection of landfill sites. Next, the fuzzy Analytic Hierarchy Process (FAHP) was used to make pairwise comparisons of selected criteria by domain experts for assigning weights to the decision criteria and to calculate their importance degree. Finally, by considering the interrelationships among the criteria, Decision-making Trial and Evaluation Laboratory (DEMATEL) technique was applied to deal with the importance and causal relationships among them, and to recognize the influential criteria of landfill site selection. Obtained results show that, the criteria of sensitive area and intra-municipality are revealed to be the top two significant influences in selecting landfill sites. By identifying the relevant criteria, the structures and interrelationships, this study can offer an insight for decision makers to understand cause-effect relationships and allow to select suitable sites.

The mobile phone has undeniably brought a paradigm shift, affecting both lives of the people and the business environment. It has permeated the lives of billions of people around the world; becoming for many an indispensable device. Moreover, adoption of mobile banking has significant impact on reducing cost and enabling change in retail banking. Factors influencing the intention to use or adopt mobile banking are a very important part, thus playing a vital role for mobile banking service providers. This study proposes and validates an online mobile banking model by integrating the technology readiness acceptance and theory of planned behaviour model, using a comprehensive set of measurement dimensions identified from the literature.

This paper attempts to develop, validate the measures for LSCP and also test the influence on the organisational performance. The data was collected through questionnaire survey from 154 transport service providers from Mumbai and nearby costal region in India. In the first phase, confirmatory factor analysis was used to test the validity of the proposed measurement scale for all the identified constructs. Second phase tests the relationship between the identified constructs and organisation performance using SEM. In doing so, we map a positive relationship between logistic supply chain performance (LSCP) and organisational performance (OP) which ultimately leads to enhance the performance improvement within firms and across the supply chain.

The purpose of this study is to present an integrated CFA-FAHPTOPSIS (CFAT) framework that uses a confirmatory factor analysis (CFA), fuzzy-analytic hierarchy process (FAHP) and technique for order preference by similarity to ideal solution (TOPSIS) for measuring multi criteria airlines service quality dimensions. The proposed CFAT framework is an integration of CFA, FAHP-TOPSIS. This paper validates the CFAT framework for measuring service quality in the Indian airline industry. For this purpose, we developed six main criteria and 28 sub-criteria based on review of literature. The validations were carried using confirmatory factor analysis and were based on data collected through a sample survey on 300 air passengers from India. Three experts were used to rank the identified criteria across four domestic airlines in India. The final ranking of the airlines were based on FAHP-TOPSIS. The study revealed that cabin service, was the highest ranked service quality dimensions followed by booking service, check in service and responsiveness. Timeliness of flight and special offers and freebies scored low on the ranking.

In a fast paced world, organisations need to push and adapt themselves to meet global demands. Supply chain operational performance (SCOP) is a vital tool used to improve business performance. This study aims to investigate measurement, development and validation of a proposed SCOP model using structural equation modelling (SEM). It conceptualises and develops four vital dimensions of SCOP. Literature review reveals information integration (II), industry characteristics (IC), supplier initiative (SI) and supply chain collaborative advantage (SCCA). Data was collected from 306 operations and supply chain heads from the auto-sector. Results prove that II, SI, IC and SCCA were found to have positive effects on SCOP with significant second order construct relationships. The instrument will help supply chain in flexibility, cost control and improved quality.

The proposed method is used in the selection of sustainable residential house using relative benchmarking (against other sustainable residential housing projects) as well as absolute benchmarking (against an ideal residential housing), which offers a tangible means by which to evaluate residential house. In light of the heterogeneous capabilities of sustainable residential housing project, the decision-makers can objectively assess each residential house interface and detect when corrective action may be necessary. A sample sustainable housing project as a strategic tool to facilitate marketing decisions system design is used to illustrate the proposed approach. Implementation results show that the proposed approach is able to eliminate the burden of quantifying qualitative concepts in sustainable quality function deployment (QFD) and model the customer variability and the design team's preference. Due to its easiness in articulating preferential information, our approach can reduce the cognitive burden of QFD planning team and give a practical convenience in the process of QFD planning.

Axial Velocity Density Ratio (AVDR) is an important parameter to check the two-dimensionality of cascade flows. It can have significant influence on the cascade performance and the secondary flow structure. In the present study, the effect of AVDR has been investigated on a highly loaded Controlled Diffusion airfoil compressor cascade. Detailed 3D Computational Fluid Dynamics (CFD) studies were carried out with the cascade at five different AVDRs. Key aerodynamic performance parameters and flow structure through the cascade were analyzed in detail. CFD results of one AVDR were validated with the experimental cascade test data and were seen to be in good agreement. Loss characteristics of the cascade varied significantly with change in AVDR. Increase in AVDR postponed the point of separation on the suction surface, produced thinner boundary layers and caused substantial drop in the pressure loss coefficient. Strong end wall vortices were noticed at AVDR of 1.177. At higher AVDRs, the flow was well guided even close to the end wall and the secondary flows diminished. The loading initially improved with increase in AVDR. Beyond a certain limit, further increase in AVDR offered no improvements to the loading but rather resulted in drop in diffusion and deviation.

The extant literature recognized the significance of attitudes in understanding an entrepreneur/intrapreneur. The present study contributes to the value addition in the extant literature in the form of developing and validating standard measures and models of entrepreneurial attitudes (EA)/intrapreneurial attitudes (IA). Our models suggest that the six attitudes, namely, achievement orientation, risk-taking propensity, internal locus of control, innovativeness, pro-activeness and market orientation (MO), have a positive impact on venture performance of both entrepreneurs and intrapreneurs. Our well-tested models and the measures of EA/IA attitudes provide a concrete foundation for future research studies of EA/IA across the historical, temporal, institutional, spatial, social and cultural contexts.

The purpose of this paper is the development of the scale for supply chain operational performance in Indian automobile sector by using exploratory factor analysis. The review highlighted enhanced use of information integration. The study also pointed out that suppliers are not only a source of materials; they could play a vital role in the creation of knowledge due to information integration, and can be a source of innovation. This outputted into strong base for collaborative supply chain. It is important for automobile organisation to understand industry characteristics of subsegments of supplier producing different products. Organisations can see directly some operational benefits by working closely with suppliers, like reduction in various costs, improve quality, and shorten lead-times by involving supplier in the vendor managed inventory and also in collaborative planning and forecasting. Further, by using exploratory factor analysis developed instrument helps supply chain practitioner to achieve enhanced efficiency levels by studying its significant effect on efficient integration on integral supply chain operation performance.

Supply chain management (SCM) is one of the tools used by organisations to improve their business performances. This research aims to investigate the relationships between supply chain management practices and organisations performance using structural equation modelling (SEM) in Indian retail sector. This research conceptualises and develops six supply chain practices viz. strategic supply partnership (SSP), customer relationship practice (CRP), lean retailing practice (LRP), information sharing (IS), information quality (IQ) and postponement practices (PP) and tests the relationship between SCM practises and SC profitability. Data for the study were collected from 162 operations and supply chain heads from leading retail store outlets in India. The results indicate that SCM practices and its impact on SC profitability were investigated and it was found that SCM practice have positive impact on SC profitability. Statistically the relationship between the second orders constructs SCMP and SCP was also found to be significant. Overall, the model has a satisfactory fit.

India witnessed significant growth in the organised retail store format in the last ten years. Since Indian shoppers’ preference to organised retail setup is growing, the Indian retail sector has caught the world’s imagination and has become attractive retail destination. One critical aspect of such mammoth growth of retail is the development of supply chains and effective supply chain practices. This study aims to design a scale with a high degree of reliability, validity and dimensionality which helps to determine appropriate supply chain practices and their interrelations. The data was collected through questionnaire survey from 157 operations and supply chain heads from leading retail stores in India. Confirmatory factor analysis was used to test the validity of the proposed measurement scale for all the major SC practices. This instrument helps supply chain practitioners to achieve enhanced efficiency levels by studying its significant effect on the efficient integration of entire supply chain process.

Selecting the right suppliers significantly reduces the purchasing cost and improves corporate competitiveness. There are various techniques for selecting suppliers/partners, such as mathematical techniques. In this paper, we relate product characteristics (engine housing for the Escorts, Maruti Suzuki, etc.) to supply chain strategy and adopt supply chain operations reference model level-I performance metrics as the decision criteria. This paper, an integrated analytic hierarchy process (AHP) and data envelopment analysis (DEA) linear programming- (LP-) based multi-criteria decision-making methodology, is then developed to take into account both qualitative and quantitative factors in supplier selection. While the AHP process matches product characteristics with supplier characteristics (using supplier ratings derived from pair-wise comparisons) to qualitatively determine supply chain strategy, DEA mathematically determines the efficient supplier from the chosen suppliers. Since DEA and LP uses AHP ratings as input, the variations of pairwise comparisons in AHP will influence the final order quantity. Therefore, users of this methodology should put greater emphasis on the AHP–DEA–LP progress to ensure the accuracy of supplier ratings and efficiency of the supplier.

Supplier-buyer strategic partnerships (SBSP) are widely considered as an effective source of competitive advantage by firm’s operating in turbulent business environments. The objective of this research is to empirically investigate whether different dimensions of environmental uncertainty have different impacts on the SBSP. The uncertain environmental factors, namely business cost, labour availability, competitive hostility, government laws and regulations, political environment, dynamism in the market (volatility and complexity) impact SBSP including specific investments. The study is based on the reposes of 270 purchasing managers from 54 manufacturing and process industries from India (Mumbai region). A structural equation modelling was used to analyse the SBSP. The results suggest a statistically significant relationship between the selected uncertain business environmental factors and the SBSP. The primary contribution of this research lies in its ability to offer practically relevant insights to aid managers in considering whether or not strategic partnership are likely to be influenced under their particular types of environmental uncertainty.

Service quality is believed to be one of the main determinants of customer satisfaction and purchase intention. However, there are very few studies that have been conducted to identify the important dimensions of service quality specific to banking sector. The present study is aimed to assess and compare the perceived level of bank service quality and to investigate the dimensions of quality banking service in private and public sector bank using an instrument banking service quality scale (BSQ) specifically designed for measuring service quality in banks. The study is based on the responses collected from 240 customers banking with private and public sector retail banks in India. The results show that the customers of public sector and private sector banks differ in terms of their service quality perceptions. Private banks are perceived to be superior on the service quality dimensions: effectiveness, access and tangibles whereas, the public sector banks score better on the dimensions of price and reliability. The study concludes that the BSQ instrument appears to be a valid instrument to measure the service quality in Indian retail banks.

A firm that manufactures and delivers a tangible product, logisticsis both a fundamental business activity and the underlying phenomenon that drives most other business processes. It is difficult to imagine BPR without logistics. In this paper, a case study on reengineering the in-plant logistics process in a Cement Manufacturing Plant (CMP) is presented. The finding of the study shows that BPR leads to improvement in the overall in-plant logistics process. It may be noted that every company will have their own way of implementing BPR based on their unique situations however the basic framework will remain the same.

The multi-criteria decision making (MCDM) problem in supplier selection involves a number of qualitative and quantitative attributes which are required to be analysed for evaluating the performance of the suppliers or at the supplier selection stage. This paper presents an integrated methodology for evaluating the supplier selection using analytical hierarchy process (AHP) and linear programming problem (LPP) model. This integrated approach is a two stage process. The first stage identifies the functional weightage scores for the selected suppliers using AHP and the second stage uses LPP, for making an optimal allocation of units to the selected suppliers. The paper shows the application of this methodology for the supplier selection situation, while purchasing the liquefied petroleum gas (LPG) and compressed natural gas (CNG) kits by the automobile manufacturing companies. The selection criteria used in the study includes quantity, on-time delivery product, quality, service, responsiveness, technical capability, production facility and pricing structure.

Supplier selection of a telecommunications system is an important problem to a telecommunications company as the telecommunications system is a long-term investment for the company and the success of telecommunications services is directly affected by the supplier selection decision (Tam and Tummala, 2001). The aim of this study is to model for supplier selection problem for a real world application in India which is the most populated country in world. A number of conflicting qualitative and often accompanied by ambiguities and vagueness. This makes fuzzy logic a more natural approach to this kind of multi-criteria decision-making (MCDM) problems. The paper proposes a combined MCDM methodology. Fuzzy analytic hierarchy process (AHP) and linear programming (LP) are utilised for assigning weights of the criteria for supplier selection and linear programming (technique for order preference by similarity to ideal solution) is used to determine the most suitable alternative using these criteria weights.

In this paper we propose an integrated model from the most important and usable multi-criteria decision-making (MCDM) techniques, means analytic hierarchy process (AHP) and quality function deployment (QFD)-fuzzy technique for preference, in order to examine the improvement fields of Indian automobile industry. A new approach, AQF method, has been suggested to combine the results of three techniques to find the final ranking. Besides, we propose a developing QFD-fuzzy model as a basis for comparing the reliability of results of the MCDM techniques, which depicts that AQF is more reliable than other MCDM techniques. Our results have certified that technology, economical aspects, style, comforts, safety, tools availability, convenience, social aspects, aesthetics view, and manufacturers are the customers’ most important criteria for automobile selection. After comparing the internal and external products, and ranking them based on the criteria and sub-criteria, the necessity to improve internal automobiles on various fields has been prioritised.