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The objective of the study is to test a conceptual model based on the interrelation between data-driven supply chain quality management practices (DDSCQMP) and the performance of organized retailing firms in India.

Based on a comprehensive review of literature, the dimensions of DDSCQMP concerning the Indian organized retail sector have been extracted. Considering the research objectives, the research data has been collected using a structured questionnaire from Indian retailers. Overall 133 questionnaires were responded successfully from retailers. The model was tested using structured equation modeling (SEM) through PLS 3.0.

The research findings confirm hypotheses and reveal the statistically significant relationship between DDSCQMP and retailers' performance at an aggregate level. However, the results of the individual-level analysis of DDSCQMP appear to vary from practice to practice. Among various DDSCQMP, “customer focus” with the highest beta (ß) value was found to have the greatest impact on performance followed by “employee relations”.

The study provides empirical justification for a structural model that identifies a positive and significant relationship between DDSCQMP and organizational performance within the context of organized retail sector of India.

The aim of this paper is to identify the criteria that are used for vendor or supplier rating, prioritize these criteria based on the industry inputs and develop a vendor rating model. The data were collected from an Indian start-up working in product development using three-dimensional printing (3DP).

Factors of importance for vendor rating were identified through industry visits, and interacting with the industry experts from the start-up under consideration, substantiated by extensive review of relevant literature. A questionnaire-based survey was carried out to further narrow down the factors important to the industry, prioritizing them with a pairwise comparison analysis as envisaged in the analytical hierarchy process (AHP) technique along with the calculation of consistency ratios. Technique for order preference by similarity to ideal solution (TOPSIS) methodology was further used for data aggregation.

This research brought forward the criteria that are useful for rating vendors or suppliers with reference to 3DP sector.

This paper integrates AHP and TOPSIS to solve a multi-criteria vendor rating problem. The attempt was made to make vendor rating process universal so that it can encompass all the vendors of the firm.

The aim of this study is to examine the impact of supply chain management (SCM) practices and retail outlet attributes on the performance of organised food retailers in India during COVID-19 pandemic.

Authors conducted empirical research with SCM practices and retail outlet attributes to evaluate the retailers’ performance. The authors present the results from 321 valid responses from the Indian food retailers. The study used structured equation modeling to present the analysis and the results.

The findings of this study reveal that most of the SCM practices (i.e. information technology, level of information sharing, customer relationship, supplier relationship and goal congruence) have a positive impact on performance except the quality of information sharing. The results show that in the time of the pandemic, the retail outlet attributes (image, service quality and convenience) have no significant relationship with the food retailer’s performance while SCM practices are necessary to achieve better performance of the food retailers.

A proactive approach is needed from retailers at the time of pandemic situations to manage the supply chains. The retailers must be extra careful in screening the suppliers for the short and long run. The reason being that in the situation of pandemic, customers might be more demanding and hence, food retailers need to pay special attention to gain growth. It is also required that the policymakers should give importance to the implementation of these SCM practices to be positioned differently.

The research can be valued in terms of its original contribution towards companies in overcoming the disruption caused by COVID-19 to maintain a balance between demand and supply and proposes a completely new theoretical framework. The proposed theoretical model would add value to the existing literature to help the retailers in process of their performance improvement. The study has provided insights for retail organisations, suppliers and government departments to manage their SCs more effectively and efficiently during the pandemic.

The present study provides evidence on export advantages of horticultural commodities based on competitiveness, trade balance and seasonality dimensions.

The study delineated horticultural commodities in terms of comparative advantage, examined temporal shifts in export advantages (mapping) and estimated seasonality. Product mapping was carried out using the Revealed Symmetric Comparative Advantage (RSCA) and Trade Balance Index (TBI). Seasonal advantages were examined through a graphical approach along with the objective tests, namely, modified QS-test (QS), Friedman-test (FT) and using a seasonal dummy.

Cucumbers/gherkins, onions, preserved vegetables, fresh grapes, shelled cashew nuts, guavas, mangoes, and spices emerged as the most favorable horticultural products. India has a strong seasonal advantage in dried onions, cucumber/gherkins, shelled cashew nut, dried capsicum, coriander, cumin, and turmeric. The untapped potential in horticulture can be addressed by handling the trade barriers effectively, particularly the sanitary and phytosanitary issues, affecting the exports. Proper policies must be enacted to facilitate the investment in advanced agricultural technologies and logistics to ensure the desired quality and cost effectiveness.

Commodity-specific studies on value chain analysis would provide valuable insights into the issues hindering exports and realizing the untapped export potential.

There is no holistic and recent study illustrating the horticulture export advantages covering a large number of commodities in the Indian context. The study would be helpful to the stakeholders for drawing useful policy implications.

The technology used by an organization is significantly influenced by the organization’s preferred competitive capabilities. The Internet of things (IoT) is an important technology, which is implemented by most prominent business organizations. The purpose of this paper is to investigate the relationship between an organization’s strategies and the IoT architectures implemented by the organization.

This study has been carried out on primary data collected with the help of a structured questionnaire. The data have been analyzed by statistical techniques like cluster analysis and discriminant analysis through SPSS.

The empirical investigation of data revealed that there is a relationship between organizational strategy and IoT architectures. The three-layered architecture of the IoT is most suitable for caretakers; the three-, four- or five- layered architectures are suitable for marketeers; whereas innovators find it more suitable to use five- or more-layered architecture of the IoT. This paper draws the conclusion based on maximum likelihood rather than using statistical analyses like ANOVA. The idea behind using the maximum likelihood estimate is that there are many subjective parameters in deciding the architectures of the IoT. These subjective parameters are difficult to quantify, so it is not possible to apply ANOVA on these parameters.

This study considers three organizational strategies; the relationship between other organizational strategies and IoT architecture will be studied in future.

This study offers multiple opportunities to practitioners and consulting firms of the IoT to adopt a suitable IoT architecture according to the organizational strategy. This study equips IoT development engineers to select suitable technology for data capturing, data transmission, and data management and access for an IoT architecture.

Although a lot of work has already been done on the architecture of IoT for different industries and businesses, to the best of our knowledge, this is the first study that relates organizational strategies to IoT architectures. This study applies to all the major industry types.

The study aims to estimate the impact of the vigilant board independence (BIND) dimension that potentially neutralises the unfair influence of chief executive officer duality (CEODU) on Indian public banks' performance.

The study takes into account the fixed-effects model to investigate the potential moderating effect of BIND in the relationship between CEODU and Indian bank performance. The econometric model is also robust against heteroscedasticity, serial correlation and cross-section dependence issues to ensure that the model is free from such biases. The study also addresses the major issue of endogeneity via vector autoregression and performs the analysis by considering one period lag of the explanatory variables.

The findings demonstrate that CEODU does not always lead to a negative outcome on the performance until or unless the board is monitored by the effective presence of outside directors.

The regulatory bodies consider the results to strengthen board capital where CEODU can benefit a business entity if vigilance BIND is present at or above a threshold point.

The study evaluated an under-researched role of BIND as a moderator that undermines the negative influence of CEODU on the performance of Indian banks. The study also establishes that the CEO's contribution to performance increases when the number of outside directors is at or above a certain threshold.

The paper aims to craft a non-parametric composite value for the board quality of Indian banks where the weights can be assigned endogenously.

The study employed a non-parametric data envelopment analysis (DEA)-based novel extension known as the benefit of doubt approach. To measure the strength of the Indian bank corporate board in terms of board efficiency (BEF), the study used a mixed approach, i.e. first, the study calculates the percentile ranks of the five attributes that the study assumes are the characteristics of the strong board including board size, number of outside directors, frequency of meetings, non-duality leadership and board gender diversity. Thereafter, the study performs the benefit-to-doubt approach to finally measure the efficiency of the board.

The findings of the study establish that the methodological framework present in the study to measure the strength of the board in terms of BEF has been a much superior method over the other weighted and non-weighted linear average methods.

This methodology aids the shareholders, investors and regulatory bodies in rating the Indian banks based on their strength in terms of better monitoring boards and ensuring a smooth agent–owner relationship.

The benefit of doubt approach has been a unique and novel methodology to craft the composite value for any multidimensional phenomenon. One of the major benefits of using this approach is that it assigns the weights endogenously to each dimension and thereafter collectively determines the efficiency of such a phenomenon.

This study aims to explore and comprehend the reasons behind individual investors’ intention towards socially responsible investment (SRI) in the Indian stock market along with examining the validity of the theory of reasoned action (TRA) model to predict such phenomenon in the Indian context.

The TRA has been used as an underlying framework and has been extended by adding four variables, namely, moral norms, environmental concern, financial literacy and financial performance. The study used a self-administered questionnaire and adopted a convenience sampling method for a survey to collect the data from the individual investors from the capital cities of three states of India. Further, the collected data have been analysed using two-step structural equation modelling.

Results of this study indicate a significant impact of attitude, subjective norms, moral norms, financial literacy and financial performance on investors’ intention towards SRI; however, no significant relation was found between environmental concern and investors’ SRI intention. The multiple squared correlation (R²) shows that the final model could explain 71% of the variance in investors’ intention towards SRI, which signifies a successful implementation of TRA model along with new additions to predict investors’ decision-making behaviour for SRI. Moreover, investors are found to be highly concerned primarily about their financial goals and then for their personal obligation towards society as far as SRI is concerned.

This study reports significant and prominent importance of subjective norms in SRI which could be a strategic theme for the government and the policymakers to influence investors through their opinion leaders to promote SRI. The government should also increase its efforts to facilitate financial literacy among citizens.

Using the TRA model and four variables, namely, moral norms, environmental concern, financial literacy and financial performance addition to its original variables, this study extends the understandings of SRI which is perhaps the novelty of this paper because such examination of SRI has not been conducted, especially in the case of developing countries such as India.

This paper aims to identify and examine the determinants for sustainable manufacturing in cement manufacturing industry in India. Further, the study examines the causal relationship between different indicators of sustainable manufacturing.

Author (s) have identified and extracted the key dimensions of sustainable manufacturing from literature. After identification of the key dimensions, analytic hierarchy process (AHP) is used to finalize the weights and further DEMATEL is used to understand the causal relationship between key dimensions.

Findings from AHP provide the weightage to the all 13 indicators of sustainable manufacturing. From AHP, it is identified that material cost has maximum weightage, whereas material consumption has minimum weightage. From DEMATEL, it is evident that occupational health safety and safety has maximum influencing variables, whereas air emission does not have any influencing variables.

The approach adopted in the study will help firms to identify the weightage of key dimensions and further the interdependency can be developed to understand the causal relationship between different indicators of sustainable manufacturing.

The purpose of this study is to quantify the supply chain flexibility for an Indian soap manufacturing firm and to measure its performance. The authors made an attempt to find key strategic and operational decision-making dimensions for developing effective supply chain flexibility environment.

The authors have extracted 11 supply chain flexibility dimensions through extensive literature review. The authors used a decision-making trial and evaluation laboratory (DEMATEL) to make causal analysis and prioritizing the dimensions. After DEMATEL analysis three major supply chain flexibility dimensions that seem to have significant amount of influence on supply chain performance of the firms were retained for further consideration. The authors have developed an excel-based template for quantitative assessment of flexibility performance indicators.

This study provides key enablers for the successful implementation of flexibility concepts in Indian soap manufacturing firms and gives a view how to measure the performance through designing template based on real data. This template can be used in other firms also by simply modifying the key attributes.

A flexibility index has been defined here with the purpose of assessing the level of flexibility vis-a-vis what is desired and is meant to be evaluated from time to time, to assess if the firm is improving its flexibility or not. The index assumes importance in view of the fact that it has been prepared based on feedbacks of both the upper and the lower management people of the firm engaged in policymaking and operations.