Purpose: The purpose of this paper is to investigate and compare what criteria novice and habitual entrepreneurs use while adding members to the founding team. Design/methodology/approach: This paper uses conjoint analysis (CA) to provide the order of preference for the “choice attributes.” The logic of CA is that even if two or more attributes influence the choice, it is unlikely that those attributes will have equal importance for founders with different entrepreneurial experiences. Findings: This paper found a significant difference in the ranking of the attributes by novice and habitual entrepreneurs. In novice entrepreneurs, the effect of direct ties in the form of kinship ties has the highest preference, followed by prior social contact and prior work relations. However, personal friendships and resource dependency received lesser importance than interpersonal attraction because of the similarity in vision, beliefs and values. Habitual entrepreneurs, however, valued resource dependency and prior work relations more than kinship ties. Also, unlike novice entrepreneurs, habitual entrepreneurs sought cofounders from their indirect ties. Practical implications: There has been an explosion of interest and funding for programs that help entrepreneurs establish a cofounding team. The authors inform these programs related to the decision concerning assisting novice and habitual entrepreneurs. Originality/value: While prior studies examined a single attribute at a time, the strength of this study lies in simultaneously tapping all attributes, along with multiple indicators for each attribute. Additionally, this study distinguishes the selection criteria of cofounders based on the entrepreneurial expertise of the lead founder. © 2022, Emerald Publishing Limited.

The pulp and paper industry is critical to global industrial and economic development. Recently, India's pulp and paper industries have been facing severe competitive challenges. The challenges have impaired the environmental performance and resulted in the closure of several operations. Assessment and prediction of the performance of the Indian pulp and paper industry using various parameters is a critical task for researchers. This study proposes a framework for performance assessment and prediction based on Data Envelopment Analysis (DEA), Artificial Neural Networks, and Deep Learning (DL) to assist industry administration and decision-making. We presented a case study based on eight industries to demonstrate the methodology's applicability. This study analyses and predicts industry performance based on sample data observations over 30 years. The result suggests the DEA-DL-based efficiency prediction has an overall MSE of 0.08 compared with the actual efficiency. Furthermore, the efficiency rankings are compared between the three techniques. The results suggest that the integrated DEA-DL method is primarily accurate in most scenarios with the actual values. The findings of this study provide a comprehensive analysis of environmental performance for policymakers. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

The purpose of the research work is to consider a multi-echelon, multi-product, and multi-modal petroleum supply chain network design problem along with its various sources of uncertainties (demand, supply, production, etc.), and to minimize both total supply chain cost and risk simultaneously. The problem is articulated as a robust optimization problem and the results are derived under various risk attitudes (viz. risk-seeking, risk-neutral and risk-averse behaviors). The non-linear problem is proposed as a Mean-Variance robust optimization problem. Two-stage stochastic programming is extended to incorporate the robustness and capture the risk aversion behavior. The scenario-based planning method is used for the estimation of uncertain parameters. A real-life case study of petroleum supply chain is conducted in the Indian scenario, considering the requisite challenges and constraints. The results show that total supply chain cost and risk demonstrate conflicting behavior with each other. Total supply chain cost increases with an increase in risk aversion level. Significant amount of operational risks can be reduced with slight increase in total supply chain cost. Penalty cost contributes the maximum to the increase in total supply chain cost along with risk aversion level. © 2022 Elsevier Ltd

Purpose: We respond to calls from business schools (B-schools), apex education bodies, regulators, activist groups and researchers for more rigorous research to understand the future strategies of B-schools in India. We specifically examine the challenges posed by the current COVID-19 pandemic (and possible future similar eventualities) and the current and long-term strategies being planned to combat such crises. Design/methodology/approach: To reveal the real-life scenario, semi-structured interviews were conducted with 22 academic leaders (Deans and Directors) of B-schools in India. These respondents were from both public and private institutions across the country. Open-ended questions were framed for exploration to help the authors understand the way forward in the Indian B-school context. Findings: Findings reveal that B-schools in India are preparing themselves to overcome short-term challenges faced due to COVID-19 as well as transforming themselves through long-term strategies. Originality/value: The study outlines strategic plans for some imaginative reassessments that B-schools may consider as a reaction to a pandemic-like emergency. The focus is on distinguishing the imperatives, creating a key guide for meeting immediate requirements, allotting assets in a prudent way to update educational course curricula and teaching methods and building the required academic infrastructure. The ability to focus on enduring changes (e.g. creating an e-learning framework and providing a safe and secure learning environment to students as per government mandates) will provide B-schools with a new lease of life in the future. © 2020, Emerald Publishing Limited.

The natural gas price is an essential financial variable that needs periodic modeling and predictive analysis for many practical implications. Macroeconomic euphoria and external uncertainty make its evolutionary patterns highly complex. We propose a two-stage granular framework to perform predictive analysis of the natural gas futures for the USA (NGF-USA) and the UK natural gas futures for the EU (NGF-UK) for pre-and during COVID-19 phases. The residuals of the previous stage are introduced as a new explanatory feature along with standard technical indicators to perform predictive tasks. The importance of the new feature is explained through the Boruta feature evaluation methodology. Maximal Overlap Discrete Wavelet Transformation (MODWT) is applied to decompose the original time-series observations of the natural gas prices to enable granular level forecasting. Random Forest is invoked on each component to fetch the respective predictions. The aggregated component-wise sums lead to final predictions. A rigorous performance assessment signifies the efficacy of the proposed framework. The results show the effectiveness of the residual as a feature in deriving accurate forecasts. The framework is highly efficient in analyzing patterns in the presence of a limited number of data points during the uncertain COVID-19 phase covering the first and second waves of the pandemic. Our findings reveal that the prediction accuracy is the best for the NGF-UK in the pre-COVID-19 period. Also, the prediction accuracy of the NGF-USA is better in the COVID-19 period than the pre-COVID-19 period. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Performance measurement activities (PMA) in the humanitarian supply chain (HSC) face several issues. Many of these issues are avoidable and inter-related, subsequently producing undesirable cascading effects. HSC Stakeholders are actively looking for means to reduce the complexities associated with PMA and improve its efficiency. In this paper, we identify and model the eleven strategies that can improve both PMA and the performance measurement system (PMS). Strategies were identified using detailed literature reviews and discussions with the experts and were modelled using the grey DEMATEL and m-TISM methodology. The results indicate that the most effective strategies are fundraising for PMA, Digital supply chain adoption, Top management support, Public awareness activities and Relief worker training. Four strategies can be grouped into the cause side and seven strategies on the effect side. The key recommendation is to rapidly adopt digital supply chain applications in the HSC. HSC stakeholders also need to pay increased attentions towards fundraising activities targeting PMS. This study advances the understanding of PMS in the context of HSC. The decision-maker can adopt the study's findings to reduce the complexities that occurred during PMA. © 2022 Elsevier Ltd

Purpose: Digital transformation (DT) leverages digital technologies to change current processes and introduce new processes in any organisation’s business model, customer/user experience and operational processes (DT pillars). Artificial intelligence (AI) plays a significant role in achieving DT. As DT is touching each sphere of humanity, AI led DT is raising many fundamental questions. These questions raise concerns for the systems deployed, how they should behave, what risks they carry, the monitoring and evaluation control we have in hand, etc. These issues call for the need to integrate ethics in AI led DT. The purpose of this study is to develop an “AI led ethical digital transformation framework”. Design/methodology/approach: Based on the literature survey, various existing business ethics decision-making models were synthesised. The authors mapped essential characteristics such as intensity and the individual, organisational and opportunity factors of ethics models with the proposed AI led ethical DT. The DT framework is evaluated using a thematic analysis of 23 expert interviews with relevant AI ethics personas from industry and society. The qualitative data of the interviews and opinion data has been analysed using MAXQDA software. Findings: The authors have explored how AI can drive the ethical DT framework and have identified the core constituents of developing an AI led ethical DT framework. Backed by established ethical theories, the paper presents how DT pillars are related and sequenced to ethical factors. This research provides the potential to examine theoretically sequenced ethical factors with practical DT pillars. Originality/value: The study establishes deduced and induced ethical value codes based on thematic analysis to develop guidelines for the pursuit of ethical DT. The authors identify four unique induced themes, namely, corporate social responsibility, perceived value, standard benchmarking and learning willingness. The comprehensive findings of this research, supported by a robust theoretical background, have substantial implications for academic research and corporate applicability. The proposed AI led ethical DT framework is unique and can be used for integrated social, technological and economic ethical research. © 2021, Emerald Publishing Limited.

This research aims to aid original equipment manufacturers (OEMs) to model, analyze, evaluate, and benchmark potential design and manufacturing suppliers based on respective product engineering teams’ efficiencies. The product engineering efficiency in this study is modeled in terms of product engineering-related attributes such as commercial lead time, number of parts, number of green features, number of end products developed, and so forth. Essentially, these parameters capture more complex interactions than simple traditional supplier selection criteria such as cost, quality, delivery, and flexibility. Due to the presence of information uncertainty in terms of bounds related to the suppliers’ related parameters, a number of data envelopment analysis (DEA) efficiency measurement models have been deployed. The proposed decision support system is novel because it models both the self-assessment type and cross-efficiency type using DEA such that maximum discrimination can be achieved amongst suppliers in the presence of interval data. The study is demonstrated for ten different sheet-metal cabin suppliers. Comparison with some well-known, relevant methods is also carried out to illustrate the validity of the proposed method. The research can specifically help supply chain managers to align the evaluation of potential suppliers with their firm's commercial considerations in the presence of information uncertainty. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

Purpose: The purpose of this paper is to empirically examine the impact of the bank-appointed directors on the agency costs of debt by using the idiosyncratic risk of stock returns as a measure of agency costs of debt. Design/methodology/approach: We use multivariate panel regression, event study and finally, propensity score matching approaches to test our hypothesis. The robustness of the results is tested for possible endogeneity issues by employing instrumental variable two-stage least square (IV-2SLS) technique. Findings: Consistent with the efficient monitoring hypothesis, we find a negative relationship between the presence of the bank-appointed director and the idiosyncratic volatility of stock returns among Indian firms. This implies that such firms take up less risky investment projects. Originality/value: We contribute to the literature from two aspects. First, to the best of our knowledge, this is the first study that examines the monitoring efficiency of creditors' governance. Hitherto, such examinations are done from the shareholders' perspective. Second, we examine the role of the bank-appointed directors on the board of non-financial firms in an emerging world context and find, contrary to the existing evidence in the US context, active monitoring role played by such directors. © 2021, Emerald Publishing Limited.

In this study, we examined the impact of change in creditors’ rights on corporate cash holdings. By using the bankruptcy code implemented in India in 2015 as a quasi-natural experimental setting, we compared the changes in excess cash in the control and treatment groups during the pre- and post-regulation periods. Our analysis revealed that the treatment firms responded to the change in creditors’ rights by decreasing their excess cash, whereas no change was observed in the control firms. This finding confirms the substitution effect that exists between external debt finance and internal cash in financing firm investments. © 2021

Using the initiation of bankruptcy reforms in India, we assess the causal effect of the bankruptcy reform on corporate risk-taking. We observe that the reform that balances the rights of creditors and debtors enables distressed firms to increase their corporate risk-taking than non-distressed firms. We next show that an increase in corporate risk-taking increases the operating performance of distressed firms, compared with non-distressed firms. These results indicate that the bankruptcy reform that favors safe viable businesses instead of forcing distressed firms to inefficient liquidation alters firms’ incentives to take the risk. © 2022 Elsevier Inc.

This study evaluates the nonlinear relationship between gender inequality and tourism receipts using a standard quantile regression approach and advances the results with an asymmetric application. Gender inequality is a pervasive and complex phenomenon rooted in the socio-economic culture of many countries. The reasons for inequality have country-specific situations, and to gain a broader understanding, countries were grouped by their income levels to explore the relationships for different groups. The study concludes that not all countries stimulate overall gender inequality through tourism. The study results show that in all but the 10th quantile, tourism had a negative and significant relationship with gender inequality providing support for the notion that tourism helps narrow the gender gap. The exceptions were found only at the 10th quantile indicates that low-income countries with low levels of tourism development could not derive the benefits of tourism’s potential in reducing gender inequality. © The Author(s) 2022.

Purpose: This study aims to examine the correlates of burnout among primary school teachers working with public schools in Chhattisgarh-India. Design/methodology/approach: Data were collected from 713 teachers using a questionnaire survey. Using partial least square path modeling, this study tests the proposed measurement and structural model. Findings: The study confirmed that general job demands and emotional job demands in a school environment significantly correlated with burnout, which, in turn, has increased somatic symptoms and decreased pro-social behavior among teachers. However, the association of burnout with absenteeism was insignificant. Emotional intelligence (EI) was found to buffer the adverse associations of general job demands and emotional job demands on burnout. Practical implications: The findings of this study demonstrate that EI has buffering effects on high job demands that consequently reduce burnout. This will help educators and policymakers in shaping and formulating effective policies and practices to deal with burnout. Originality/value: Earlier studies exploring burnout of primary school teachers, especially in the Indian context, had focused exclusively on demographic factors. This study is an early attempt to understand the impact of contextual factors on burnout thereby helping in designing appropriate interventions thereof. This study additionally rationalizes the unexplored association of burnout with pro-social behavior among educators. © 2021, Emerald Publishing Limited.

This study investigates the impact of COVID-19 on the US equity market during the first wave of Coronavirus using a wide range of econometric and machine learning approaches. To this end, we use both daily data related to the US equity market sectors and data about the COVID-19 news over January 1, 2020-March 20, 2020. Accordingly, we show that at an early stage of the outbreak, global COVID-19s fears have impacted the US equity market even differently across sectors. Further, we also find that, as the pandemic gradually intensified its footprint in the US, local fears manifested by daily infections emerged more powerfully compared to its global counterpart in impairing the short-term dynamics of US equity markets. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Store pricing policy helps consumers to form perceptions about the products as well as the store. We study two commonly used pricing policies, EDLP and HiLo from the customers’ point of view. We break down these policies based the amount of variability and the degree of predictability. Consumers form perceptions of price fairness and store trust based on these pricing policies and consequently decide their purchase intentions. We observe that price fairness perceptions mediate between variability of pricing and purchase intention. Different pricing policies are likely to attract different types of consumers. Some customers are likely to be driven by deals and discounts while others are not. We show that trust mediates between variability and predictability of pricing and purchase intention only for customers who are low on deal proneness. Our study contributes to the literature of pricing policy by viewing promotion policy from the perspective of its elements—variability and predictability. © 2022, The Author(s), under exclusive licence to Springer Nature Limited.

Purpose: This study aims to examine the impact of green operation (measured using the energy intensity of its operations) on the value of corporate firms in stock markets. The authors also examine the channel of such an impact and its implication on a firm's financing choices. Design/methodology/approach: The authors conduct various univariate and multivariate regression analyses on a panel of all non-financial Indian firms listed on the National Stock Exchange from 2010 through 2018. The authors use the sensitivity of investments to the cash flows model to test the financial constraints hypothesis. Findings: The authors’ analysis shows a positive relationship between energy efficiency (firms that consume a lesser amount of energy per unit of sale) and the value of firms in the stock market. The authors empirically attribute this greater valuation to the lesser volatility of stock returns, measured by the standard deviation of daily stock returns. Finally, the authors observe that investments in energy-efficient firms are less sensitive to their internal cash flows. Practical implications: The results suggest that less green firms face greater constraints in accessing finance from external sources and, therefore, depend more on internal than external capital to finance their investments. Hence, managers of such firms can ease their financing pressures by making their operations greener. Originality/value: In this study, the authors examine the implications of green operations on the financing choices of firms. This aspect of going green is important because managers will have enough incentives to invest in green technologies as that would increase their access to external finance and, hence, decrease their financial constraints. © 2022, Emerald Publishing Limited.

The COVID-19 outbreak and the subsequent lockdown were an unanticipated shock to the global stock market. Managers also had minimal time to counterbalance its effect through corporate policies. Therefore, this health crisis offers a unique opportunity to examine the effect of corporate social responsibility (CSR) on shareholder value. We observe that firms engaged in more CSR activities outperform other firms. This suggests that CSR plays a positive role in determining shareholder value, particularly for an emerging market where minority shareholder rights are weak. Collaborating with our main finding, we further find that governance metrics play a significant role. © 2021 International Review of Finance Ltd.

Extending the notion that reshoring can have a significant impact on a firm's supply network owing to the associated location decisions, we explore how reshoring influences the resilience and sustainability of a focal firm's supply network. While reshoring is triggered by aspects related to both the home (domestic) and the host (foreign) country, frequently more favourable aspects in the home country lead to the reshoring decision. To investigate these dynamics, we construct two large-scale networks consisting of 2066 and 1283 firms, respectively, capturing the supply networks of Apple and Jaguar Land Rover. Both networks have been experiencing the reshoring of previously foreign suppliers to domestic locations. Our investigation captures the network dynamics created by this relocation of tier 1 suppliers for the overall supply chain network, that is, also for higher-tier/sub-tier suppliers. The results reveal, contrary to our expectations, that indirect (sub-tier) foreign suppliers positively influence the network's resilience, with this impact, however, being negatively moderated by their degree centrality, that is, the number of ties a node possesses. In addition, existing indirect (sub-tier) domestic suppliers do not have a significant influence on the resilience of the network. No evidence was found for the impact of reshoring on sustainability. Overall, our study contributes to the reshoring literature by delineating its influence on both the resilience and the sustainability of a focal firm's supply chain network. British Journal of Management© 2022 The Authors. British Journal of Management published by John Wiley & Sons Ltd on behalf of British Academy of Management.

This study examines whether societal trust diminishes the role that debt plays to mitigate agency problems between managers and shareholders. Using data from 46 countries, we find that societal trust is inversely associated with leverage ratio. Our results are robust to a battery of robustness tests. We also observe that societal trust can substitute for formal institutions, and therefore, the impact of societal trust is weaker for firms located in countries with strong legal institutions. Overall, our study emphasizes the role of informal institutions like societal trust in resolving agency problems stemming from the conflict of interest between shareholders and managers. © 2021 Elsevier B.V.

Most studies on performance evaluation in the hospitality industry solely focus on efficiency measurement; however, effectiveness, an integral part of organizational performance that can influence its competitive stance in the market, is ignored. Therefore, this study aims to measure the performance of Indian hotels considering both efficiency and effectiveness simultaneously using a two-phase evaluation model with panel data. The efficiency and effectiveness scores are measured using data envelopment analysis. McKinsey’s nine-cell matrix has also been deployed to show the competitive positioning of the hotels being studied. The results yield no significant correlation between the efficiency and effectiveness scores; nevertheless, there does seem to be a strong positive correlation between effectiveness scores vis a vis the overall performance of a hotel per se. © 2020 Taylor & Francis Group, LLC.