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In recent years, there has been a growing emphasis on competency-based systems as a means of assessing employee performance. These systems assess the degree to which the competencies of employees align with the requirements of their employment positions. This study aims to identify, prioritize, and make contextual interrelationships of the competency dimensions that are relevant for evaluating employees in the context of Indian manufacturing MSMEs.

These dimensions were identified through an extensive literature review and interviews with industry experts. Further, a mixed-methods approach, including the “Bayesian Best-Worst Method” (BBWM), is applied for prioritizing important dimensions, whereas for making mutual relationships, the “Interpretive Structural Modeling” (ISM) method is utilized. “Matrice d'impacts croisés multiplication appliquée á un classment” (MICMAC) is also known as “cross-impact matrix multiplication applied to classification” is used for clustering competency dimensions based on their “driving power” and “dependence power”.

The findings reveal that among the primary dimensions, “creative performance,” and among the sub-dimensions, “innovative behaviors,” are the most critical competency dimensions for an employee assessment. The study also found that “smart working”, “factual and theoretical knowledge”, “empathy at work”, “understanding of specific knowledge”, and “engagement ideas and activities” are the main dimensions driving employees' competency.

This paper provides contribution to the competence literature by identifying and evaluating competency dimensions for assessing employees' performance within manufacturing MSMEs in an emerging economy such as India. The study also assesses the rank and contextual relationship between the identified dimensions as no past research focused on the same by using BBWM and ISM in the Indian manufacturing MSMEs context.

Understand the external environment and trends impacting customer preferences. Understanding the elements of customer segmentation and positioning for products such as backpacks and travel luggage. Understand the levers for turnaround management. Qualitative evaluation of an opportunity for investment – greenfield versus brownfield. Developing a marketing plan for growth.

Indian Luggage market has an oligopoly structure with three major brands – very important person (VIP) Industries, Samsonite and Safari Industries Ltd. (SIL), holding around 90% share of the organized market. The market had evolved slowly, with the players offering limited assortment and having limited manufacturing capacities in India. SIL, having been in business for nearly 25 years, had been registering a flat top line. In 2011, the top management shuffle at VIP Industries witnessed the exit of the then MD, Mr Sudhir Jatia. Mr Jatia decided to acquire the majority stake of 56.55% for Rs 29 crores for the struggling SIL. What followed in the subsequent years was the resurgence of SIL to a noteworthy position in the industry. From a merely 2% market share in 2011, SIL went on to hold nearly 16% market share in 2019. This growth in market share, along with CAGR of almost 15% for the luggage market overall, has boosted the revenue of SIL by nearly 10-folds from INR 620m in 2011 to INR 5.73bn in the year 2018. Several reasons had been identified behind the growth of this company, such as – Mr Jatia’s leadership style, focus on profitable stock keeping units, acquisition of other brands, operational efficiency and financial infusion. However, the larger question was that – Will SIL, which had been following a challenger strategy to date, be able to overcome the leaders in the industry? What strategies should it pursue now? And what obstacles can it expect on this anticipated journey of growth?

Undergraduate and post-graduate.

Teaching Notes are available for educators only.

CSS 11: Strategy.

Innovation is a prerequisite for economic and technological growth of any organization. Identifying enablers of innovation can help managers accelerate the process of economic growth. The purpose of this paper is to identify the prominent enablers of innovation in small and medium enterprises (SMEs) that can help overhauling organizations and benefit them economically.

A comprehensive literature review and expert’s opinions have been applied to identify enablers of innovation. A case of automotive component supplier is considered for conducting the research. A coalescence of Grey and DEMATEL methodologies has been incorporated to first rank the enablers of innovation based on their importance and then identify the causal relationship among these enablers by characterizing enablers into causal and effect groups.

A few important enablers, namely, entrepreneur traits, knowledge management, resources for innovation, and linkage capabilities, have been identified as prominent enablers for successful innovation in SMEs.

This paper identifies enablers of innovation in SMEs and the causal relationship between these enablers. The identified enablers and the causal relationship between these enablers will help managers of small organizations in selecting the enablers that need to be focused on, which, in turn, can drive other enablers of innovation, thus saving time and resources of the organizations.

This paper uses a novel Grey–DEMATEL methodology to identify the causal relationship among enablers and also contributes to the literature on innovation by identifying enablers of innovation in SMEs.

The purpose of this paper is to identify and prioritise supply chain finance (SCF) adoption enablers and develop a novel comprehensive framework to select supplier firms based on their SCF adoption capability.

The study deploys a three-phase method to identify and prioritise SCF adoption enablers, followed by developing a model to select suppliers according to their SCF adoption capability. An extensive literature review, followed by a Delphi approach-based expert interview, has been used to finalise the enablers. Using the Best Worst Method and the VIsekriterijumsko KOmpromisno Rangiranje technique, a supplier selection model has been developed in the context of a case company.

The financial health and technological advancement variables received the top priority, followed by collaborative efficiency, whereas the human resources and organisational variables received the slightest significance. A supplier selection framework has also been developed by using the adoption capability of these factors by the supplier partners. In this study’s model, Supplier 4 exhibited better SCF adoption capability and received the top priority.

Manufacturing supply chains in a developing country are the scope of the current study. Extensive future studies are required to derive a global consensus.

The proposed framework of this study can be used to select supplier firms based on their SCF adoption capability. Policymakers can emphasise the most critical enablers of SCF adoption to assist small supplier firms to be a part of the advanced global supply chains.

The current study established a novel comprehensive framework for supplier selection based on the Supply Chain Finance adoption capability of MSME supplier firms.

Technology and knowledge have become the buzzwords of the new millennium. Technological changes and demanding customers are creating a more knowledge intensive, turbulent, complex and uncertain environment. Organizations, which are able to continually build faster and cheaper new strategic assets than their competitors, create long-term competitive advantages. Thus, the growth of companies is directly associated with innovativeness and technological development, especially for small organizations that are more vulnerable to dynamic changes in market place. Organizations need a strategic framework that can help them to achieve the goal of technology development and competitiveness. The purpose of this paper is to develop such strategic framework for small organizations for their technology development and, hence, survival in marketplace.

Options field methodology, options profile methodology, analytic hierarchy process (AHP) and fuzzy set theory are utilized to generate various options and profiles to propose a conceptual framework for technology development.

The results from the study showed that “mixed approach,” “strategic simulation approach” and the “regulatory environment approach,” in this order, emerged as the top three important options for the strategic technological development of small manufacturing enterprises.

This result can provide an original and more accurate implementation pathway toward technological innovative development in emerging economies. The proposed framework can provide valuable guidelines and recommendations to practicing managers and analysts for policy development to promote innovative and technological developments.

The catastrophic effects of the COVID-19 pandemic have considerably impacted the labour market and increased job insecurity among workers. This study systematically reviews the literature on job insecurity conducted in the context of the COVID-19 pandemic with three key objectives. First, to identify the key antecedents of job insecurity during the pandemic. Second, to identify the outcomes associated with job insecurity during the pandemic. Third, to identify the underlying boundary conditions that strengthened or alleviated the association between the antecedents of job insecurity and its associated outcomes.

The study followed PRISMA 2020 guidelines for the selection and inclusion of scientific literature by systematically searching five electronic databases, namely, Scopus, ScienceDirect, PubMed, Web of Science and Psych Info.

A perception of health-related risks, negative economic consequences and organizational restructuring during the pandemic were the primary factors contributing to job insecurity among workers. The consequences encompassed detrimental impacts on health and well-being, proactive measures undertaken by employees to alleviate the threat of job loss, and a variety of tactics employed to cope with stress arising from job insecurity. The boundary conditions elucidate the factors that alleviated job insecurity among workers and influenced both their work and non-work outcomes.

This is the first systematic review summarizing the literature on employees' experiences with job insecurity amid the COVID-19 pandemic. Based on a systematic review, this study provides doable steps that HR managers can take to effectively manage job insecurity among workers, particularly during a crisis.

The pressing issues of climate change and environmental degradation call for a reevaluation of how we approach economic activities. Both leaders and corporations are now shifting their focus, toward adopting practices and embracing the concept of circular economy (CE). Within this context, the Food and Beverage (F&B) sector, which significantly contributes to greenhouse gas (GHG) emissions, holds the potential for undergoing transformations. This study aims to explore the role that Artificial Intelligence (AI) can play in facilitating the adoption of CE principles, within the F&B sector.

This research employs the Best Worst Method, a technique in multi-criteria decision-making. It focuses on identifying and ranking the challenges in implementing AI-driven CE in the F&B sector, with expert insights enhancing the ranking’s credibility and precision.

The study reveals and prioritizes barriers to AI-supported CE in the F&B sector and offers actionable insights. It also outlines strategies to overcome these barriers, providing a targeted roadmap for businesses seeking sustainable practices.

This research is socially significant as it supports the F&B industry’s shift to sustainable practices. It identifies key barriers and solutions, contributing to global climate change mitigation and sustainable development.

The research addresses a gap in literature at the intersection of AI and CE in the F&B sector. It introduces a system to rank challenges and strategies, offering distinct insights for academia and industry stakeholders.

Sustainability trends have changed the modus operandi in businesses even as the market environment becomes more socially conscious. However, relatively little research has been conducted on integrating social sustainability aspects with a focus on corporate social responsibility (CSR) into the selection of suppliers in the service sector, particularly the banking industry. In this paper, this study aims to propose a CSR decision support methodology to evaluate and prioritize socially responsible suppliers.

A novel integrated decision support methodology composed of Shannon Entropy and TOmada de Decisão Interativa e Multicritério (TODIM) methods is introduced. The Shannon-Entropy approach is used to estimate CSR factor weights, and TODIM is used to rank the suppliers, with the process completed in a group decision setting.

A Nigerian bank was used as a case study to test and show the usefulness of the CSR-based decision framework in evaluating and selecting socially responsible suppliers. The results show the topmost ranked suppliers that are recommended for future negotiations by the case (bank). The study will enable banks to select socially responsible suppliers, which could accelerate the attainment of sustainability objectives, protect their reputations and improve competitiveness.

This study pioneers the application of a novel decision methodology based on Shannon Entropy and TODIM in selecting socially sustainable suppliers in the Banking sector of an African emerging economy-Nigeria.

In recent years, “Corporate Social Responsibility” (CSR) has gained significant traction as a strategic concept embraced by business managers. However, there remains a dearth of comprehensive research exploring the impact of CSR on “Green Entrepreneurial Orientation” (GEO), a firm’s sustainability performance, and their interplay with other influential factors. Therefore, this study aims to explore how CSR, “Policy Awareness” (PA), and “Personal Innovativeness” (PI) influence GEO and “Sustainable Performance” (SP). The research also delves into understanding the mediating role of GEO and how this mediation is moderated by “Green Innovation” (GI).

Drawing from the “natural resource-based view” (NRBV) theory and employing “partial least square structural equation modeling” (PLS-SEM), the study analyzed a sample of 137 Indian manufacturing “micro, small, and medium enterprises” (MSMEs).

The results underscore the positive associations of CSR and PA with both GEO and SP. Additionally, the findings highlight the moderating effects of GI in enhancing firms' sustainability performance. The moderated mediation analysis reveals that CSR significantly contributes to SP by fostering the adoption of GEO.

These study outcomes offer valuable insights for policymakers, managers, and entrepreneurs, emphasizing the importance of crafting effective CSR strategies intertwined with innovativeness to cultivate a conducive green entrepreneurial ecosystem in businesses aligned with sustainable development goals.

There is a paucity of research on the determinants of GEO within the context of manufacturing MSMEs, especially in developing and underdeveloped nations. Furthermore, no previous study has delved into the factors that underlie GEO using a moderated mediation framework, particularly within the Indian manufacturing MSMEs landscape.

The objective of this study is to systematically identify, categorize and assess the driving factors and interdependencies associated with various types of healthcare waste. The study specifically focuses on waste that has been managed or is recommended for treatment through the application of Lean Six Sigma (LSS) methodologies.

To accomplish the study’s objectives, interpretive structural modeling (ISM) was utilized. This analytical tool aided in quantifying the driving power and dependencies of each form of healthcare waste, referred to as “enablers,” as well as their related variables. As a result, these enablers were classified into four distinct categories: autonomous, dependent, linkage and drivers or independents.

In the healthcare sector, the “high cost” (HC) emerges as an autonomous variable, operating with substantial independence. Conversely, variables such as skill wastage, poor service quality and low patient satisfaction are identified as dependent variables. These are distinguished by their low driving power and high dependency. On the flip side, variables related to transportation, production, processing and defect waste manifest strong driving forces and minimal dependencies, categorizing them as independent factors. Notably, inventory waste (IW) is highlighted as a salient issue within the healthcare domain, given its propensity to engender additional forms of waste.

Employing the ISM model, along with comprehensive case study analyses, provides a detailed framework for examining the complex hierarchies of waste existing within the healthcare sector. This methodological approach equips healthcare leaders with the tools to accurately pinpoint and eliminate unnecessary expenditures, thereby optimizing operational efficiency and enhancing patient satisfaction. Of particular significance, the study calls attention to the key role of IW, which often acts as a trigger for other forms of waste in the sector, thus identifying a crucial area requiring focused intervention and improvement.

This research reveals new insights into how waste variables are structured in healthcare, offering a useful guide for managers looking to make their waste-reduction strategies more efficient. These insights are highly relevant not just for healthcare providers but also for the administrators and researchers who are helping to shape the industry. Using the classification and ranking model developed in this study, healthcare organizations can more easily spot and address common types of waste. In addition, the model serves as a useful tool for practitioners, helping them gain a deeper, more detailed understanding of how different factors are connected in efforts to reduce waste.