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The paper aims to clarify the relationship of various enablers of supply chain (SC) management like lean enablers, agile enablers and leagile enablers. It proposes modeling the enablers to find the most appropriate strategy or methodology for determining the lean enabled SC agility.

The paper proposed the fuzzy SWARA-WASPAS methodology for determining the role of lean in enabling the SC agility. Also in continuation the AHP methodology is applied to find the priority weightage and ranking of leagile enablers, and a comparative analysis is done to select the best approach among the above two methodologies so that it would be beneficial for all the stakeholders.

The paper provides the investigation and identification of 28 lean enablers, 11 agile factors which are highly responsible to affect any SC specially focusing of automobile sector. Apart from above 9 leagile enablers were also identified in the paper. Finally, the comparative analysis has been done in the results obtained by two methodologies – AHP & fuzzy SWARA-WASPAS – to determine the lean enabled SC agility, and also to which strategy should be adopted by the organizations as per the customized requirement of their SC.

The research limitation is that in future, there may be more number of lean, agile and leagile enablers which may be explored by different researchers in their findings, which may vary the output result accordingly. Though the research implications focus on having an advantage and impact on all aspects whether it is social, economic or commercial, there is a possibility of exploration of new and better decision-making tools and approaches in future. Also, the researchers are encouraged to test the proposed propositions further by taking case study of any automobile manufacturing organizations for the validation of the results.

The paper includes implications for the development of a powerful interrelationships between lean enablers, agile enablers and leagile enablers, which will help organization and the managers to take decisions regarding selection of best strategy appropriate to them to enhance their SC. This will also help new researchers of the field to take help of the research findings for exploring new and better optimization tools and techniques in future.

The findings of the research work will definitely help society, as the successful implementation of the lean, agile or leagile strategies in their SC system will leads to an increase in their efficiency and productivity, which will ultimately results in huge advantage to all the stakeholders directly or indirectly connected with the organization. The productivity dynamics cycle will also improve which will lead to more benefits to all in the market and achieving higher living index with better living standards.

This paper fulfills an identified need to study the various enablers of lean, agile and leagile SC, as well as their interrelationships. Also there is a need to understand the importance and effect of lean in enabling the SC agility.

Employees may adopt deceptive knowledge hiding (DKH) due to nonworking time information and communication technology (ICT) demands. Drawing from the conservation of resources (COR) theory, this study aims to develop and test a model of deceptive knowledge hiding (DKH) due to nonworking time information and communication technology (ICT) demands.

In total, 300 service employees have joined the three-wave surveys. Path analysis and bootstrapping methods were used to test the theoretical model.

Results suggest that knowledge requests during nonworking time could deplete employees’ resources and increase their tendency to engage in DKH, whereas work recovery and emotional exhaustion mediate this relationship. In addition, employees’ work–family segmentation preferences (WFSP) were found to moderate the direct effects of nonworking time ICT demands on employees’ work recovery and emotional exhaustion and the indirect effects of knowledge requests after working hours on DKH through employees’ work recovery and emotional exhaustion.

First, the findings of this study shed light on the relationship between knowledge requests during employees’ nonworking time and knowledge hiding, suggesting that knowledge hiding could occur beyond working hours. Second, drawing on COR theory, this study explored two joint processes of resource replenishment failure and depletion and how nonworking time ICT demands trigger knowledge hiding. Third, the interaction effect of individuals’ WFSP and nonworking time factors on knowledge hiding deepens the understanding of when nonworking time ICT demands may induce knowledge hiding through various processes.

Emerging from the COVID-19 pandemic, the Philippines has undergone the “new normal” transition, creating a strategic recovery effort to reinvigorate the industry. In tourism, these transitions aim to safeguard employees' and guests' health and safety, ensure continuity of business operations, boost tourism confidence leading to satisfaction, and establish a resilient and sustainable tourism industry in the postpandemic era. Hence, this chapter employs a system thinking leveraging a causal loop diagram (CLD) to construct a comprehensive roadmap for Philippine tourism's postpandemic resurgence through the system thinking lens. The CLD visually illustrates the inter-related factors influencing the recovery process, encompassing collaborative engagements, innovations, economic revitalization, and health and safety protocols. By analyzing the causal relationships among these variables, this chapter explicates the dynamic and interconnected nature of the postpandemic recovery leading to the recovery of the Philippine tourism industry, especially in the context of thinking small. Through this chapter, thinking small could involve a shift toward localized solutions and community-focused initiatives that allow them to foster local economies, build resilience, and create a more inclusive and sustainable postpandemic recovery.

COVID entered the world in 2019 as a pandemic and the intensity of this health crisis is only increasing in several regions. Therefore, it is critical to study and detect the public's frame of mind, government and economists' perception regarding the COVID crisis, as well as the primary worries that the public has expressed, and how this evolves over time. Responsive measures towards COVID-19 from the Indian economy have been explored as a key objective. Moreover, efforts have been made to explore recovery in India through economists and policymakers. Data have been explored through online interviews of key economists which were published in leading newspapers and covered through media channels such as NDTV, CNBC, etc. Moreover, various newspapers and reports were explored to understand government initiatives to address COVID-19 in India. The study's findings show how essential economic recovery from the second wave is in India, and how it may be achieved by strong fiscal and monetary policies, as well as specific attention to impoverished households, small and micro-businesses and increased employment. The short-term focus of the developing economic strategy must be on giving crisis relief to the most unprotected segments of society since long-term system stimulation is impossible.

The purpose of this study is to extract factors enabling the digital car sharing enterprises' supply chain resilience (SCR), to interpret different factor prioritizations in terms of industry representatives’ assessments and specialties, and to discuss the results by applying and comparing different ranking techniques.

To achieve the purpose, the factors were identified via an in-depth systematic literature review, and next, these factors were examined by industry representatives to gather the decision matrices, then analytic hierarchy process (AHP) and measuring attractiveness by a categorical based evaluation technique (MACBETH) were applied separately to model the decision problem, and finally the findings were interpreted with different participants’ perspectives.

The findings revealed that the AHP and MACBETH provide nearly identical rankings in terms of main factors by implying the significance of the triple bottom line of sustainability. Therefore, the economic, social, and environmental dimensions of sustainability should be accomplished to obtain a resilient digital car sharing enterprise supply chain. In addition, readiness and agility are the other important factors affecting the enterprises’ resilience, and finally, although digitalization seemed to be the least important one, its sub-factor emerged at the top of the ranking list.

Up to the authors’ knowledge, this is the first study in the literature that focuses on the SCR of car sharing companies, a particular type of digital enterprise, and uses AHP and MACBETH to examine the important factors that might affect the SCR of these companies. Practitioners should take the findings of both methods into account when evaluating the results and determine the short- and long-term strategies accordingly.

Quality 4.0 is essential to the Industry 4.0 framework, notably in the electronics sector. It evaluates product quality in real-time using automatic process controls, quality tools and procedures. The implementation of Quality 4.0 criteria in the electronics industry is the subject of this study’s investigation and analysis. In this study, nine Customer Requirements (CRs) and 18 Design Requirements (DRs) have been defined to adopt Quality 4.0, aiming to increase yield while reducing defects. This study has developed a Quality 4.0 framework for effective implementation, incorporating the People, Process and Technology categories.

Many CRs and DRs of Quality 4.0 exhibit interdependencies. The Analytic Network Process (ANP) considers interdependencies among the criteria at various levels. Quality Function Deployment (QFD) can capture the customer’s voice, which is particularly important in Quality 4.0. Therefore, in this research, we use an integrated ANP-QFD methodology for prioritizing DRs based on the customers' needs and preferences, ultimately leading to better product and service development.

According to the research findings, the most critical consumer criteria for Quality 4.0 in the electronics sector are automatic systems, connectivity, compliance and leadership. The Intelligent Internet of Things (IIOTs) has emerged as the most significant design requirement that enables effective control in production. It is observed that robotics process automation and a workforce aligned with Quality 4.0 also play crucial roles.

Existing literature does not include studies on identifying CRs and DRs for implementing Quality 4.0 in the electronics industry. To address this gap, we propose a framework to integrate real-time quality measures into the Industry 4.0 context, thereby facilitating the implementation of Quality 4.0 in the electronics industry. This study can provide valuable insights for industry practitioners to implement Quality 4.0 effectively in their organizations.

This study aims to explore the strategic decisions at innovation level implemented by firms to thrive and transform themselves during crises. This study also aims to provide insights to answer the question: Why do some firms decide to implement certain types of innovation during a crisis?

This research was carried out through a multiple case study involving 22 firms. The methods were implemented in three steps to increase rigor and the replication of the study: identification and selection of cases, data collection through interviews triangulated with online information and analysis based on aggregating themes and finding patterns.

In the face of the COVID-19 pandemic, the companies analyzed focused their activities mainly on developing new features or functionalities for their products or services. Most of the firms implemented innovations across nearly all ten categories outlined by Keeley et al. (2013). Many of the implemented innovations involved personalized and superior service enhancements, process efficiency optimizations, channel diversification initiatives and new ways to collaborate to generate value. In general, the main drivers that led firms to decide to implement these innovations include reducing costs, enhancing operational efficiency, generating new revenue streams, augmenting sales and enhancing client relationships.

This research significantly advances the convergence of innovation, strategy and crisis in three impactful ways. First, it constructs a pragmatic and evidence-based framework, consolidating the primary catalysts, innovation categories and strategies adopted by firms in response to the challenges posed by the COVID-19 crisis. Second, it offers insights for guiding decision-making processes related to innovation, presenting actionable recommendations derived from the study’s findings. Thirdly, this study highlights critical perspectives that can guide governmental intervention, facilitating the formulation of more tailored and effective policies to assist companies during crisis periods.

This study centers on developing countries, specifically examining Colombian firms, considering their unique characteristics and priorities. Surprisingly, there is a scarcity of studies delving into the innovation and transformation of firms during the COVID-19 crisis in nations sharing cultural, economic and political similarities with Colombia.

This study explores the configurations of management control systems (MCSs) while taking into account entrepreneurial cognition styles (ECSs) in small and medium enterprises (SMEs). The objective is to understand the impact of ECS on deployment and identify the various modes of MCS configurations employed by SMEs. The authors draw on and synthesise two theoretical perspectives relating to cognition and management control packages to understand the associations between ECS and MCS employed by SMEs in managing their business. This study was conducted using a quantitative approach that utilises a questionnaire survey to collect cross-sectional data from 150 SMEs. The authors uncovered three cognitive styles: knowing (e.g. preciseness), planning (e.g. organising), and creativity (e.g. innovativeness). Furthermore, five configurations of MCS utilised by SMEs were identified: customer focus, performance monitoring, administrative focus, strategic focus, and development focus. By combining both analyses, the authors discovered three constellations of significant association between ECS and MCS characterised by Cluster 1’s cohesive integration approach, Cluster 2’s revealing strategic approach, and Cluster 3’s multifaceted exploration. The study is significant because it uncovers the complex relationship between ECS and MCS configurations, highlighting their interdependence within the institutional context. Using a cognitive view, the authors explore how the cognitive styles of entrepreneurs facilitated imprinting institutional context into MCS configurations. These insights enable us to envisage that ECS is not mutually exclusive but forms a continuum that provides more plausible explanations that relax the direct universal relationship between MCS configurations and contextual factors.

Value-based healthcare suggested using patient-reported information to complement the information available in the medical records and administrative healthcare data to provide insights into patients' perceptions of satisfaction, experience and self-reported outcomes. However, little attention has been devoted to questions about factors fostering the use of patient-reported information to create value at the system level.

Action research design is carried out to elicit possible triggers using the case of patient-reported experience and outcome data for breast cancer women along their clinical pathway in the clinical breast network of Tuscany (Italy).

The case shows that communication and engagement of multi-stakeholder representation are needed for making information actionable in a multi-level, multispecialty care pathway organized in a clinical network; moreover, political and managerial support from higher level governance is a stimulus for legitimizing the use for quality improvement. At the organizational level, an external facilitator disclosing and discussing real-world uses of collected data is a trigger to link measures to action. Also, clinical champion(s) and clear goals are key success factors. Nonetheless, resource munificent and dedicated information support tools together with education and learning routines are enabling factors.

Current literature focuses on key factors that impact performance information use often considering unidimensional performance and internal sources of information. The use of patient/user-reported information is not yet well-studied especially in supporting quality improvement in multi-stakeholder governance. The work appears relevant for the implications it carries, especially for policymakers and public sector managers when confronting the gap in patient-reported measures for quality improvement.

As part of the scale development process, this paper aims to test a scale to measure organizational resilience for the oil and gas industry. The objective is to provide stakeholders with a set of indicators to evaluate their organizations and prepare them to cope with the negative consequences of disruptions (e.g. Covid-19, shortage of resources, etc.).

The paper conducts exploratory and confirmatory factor analysis to test the suitability, dimensionality and reliability of specific indicators and their items under examination. Therefore, the goal is not to validate hypotheses by testing an organizational resilience scale in the oil and gas industry.

The study tests and proposes a scale to effectively measure organizational resilience within the oil and gas industry. A comprehensive set of ten indicators and 40 items are identified through this process. The findings of this research provide stakeholders in this sector with a rigorous set of indicators to evaluate the strengths and weaknesses of their organizations and better prepare them to handle disruptions.

This paper fills the gap in existing research by testing and proposing a scale to measure organizational resilience specifically for the oil and gas industry. It highlights the importance of organizational resilience for survival in a sector that is especially susceptible to disruptions.