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This study investigates the quantitative aspect of the various strains of operational excellence (OE) and competitive-potential (CP) in the SME sector. It has five steps, i.e., identifying the key performance constructs of OE and their hypothesized relationship pattern from literature, validating these constructs through factor analysis, formalizing their empirical relationships by structural-equation-modeling (SEM), path analysis of performance constructs with the empirical results, and lastly proposing a framework for OE deployment in SMEs.

Data for the deployment scores of operational excellence procedures (OEPs) were collected through a structured questionnaire survey. Nine hundred participants from a stratified random sample were approached for the survey, and 473 responses were received. Sample stratification was based on Gender, Education, Experience, Position, Department and Industry. Respondents had 5–30 years of experience managing manufacturing operations, holding the manager position and above.

The path analysis of the structural model provides unique insights into OE's practical aspects in SMEs (small and medium enterprises). For example, Contractual-conformance and Process-efficiency play pivotal roles as both have a significant positive impact on CP. Supplier efficacy, Consistency and Product-excellence do not improve CP unless mediated by Contractual-conformance or Process-efficiency.

The study provides important implications for academia, policymakers and managers. The study identifies and validates the operational excellence key performance practices and proposes a framework for manufacturing organizations. SME managers can follow the framework to develop effective operational excellence strategies to help them achieve their organizational goals. Additionally, the study emphasizes the need for continuous culture in SMEs, which will help to support operational excellence deployment. Overall, the implications presented in the study will help SMEs to enhance their competitiveness and operational performance.

The study explores the empirical investigation of the operational excellence deployment in SMEs. The study uses a mixed method approach for research design, including qualitative and quantitative approaches, and uses SEM to test the proposed framework. Validation of OE's six key performance constructs and establishing their empirical relation is an attempt to advance the Operations excellence theory. Unlike large enterprises, SMEs demonstrate an incohesive response to the practices pertaining to Supplier efficacy, Consistency and Product-excellence. This unique response pattern requires special treatment, which is incorporated into the proposed framework.

This study aims to demonstrate the importance of organizational networks in organizational performance is relatively rich; less understood are processes in organizational networking that entrepreneurs and organizations use in making sense of rapidly changing contexts for organizational performance.

This study conducts an exploratory organizational-level narrative analysis into firms’ experiences in two major emerging markets (EMs), namely, Russia and India – to identify organizational networking processes in the midst of institutional upheavals. The study is based on in-depth case studies of firms in EMs sourced from interview data from senior management and consolidated with secondary data.

The authors find that initially firms rely on informal networks (including blat/svyazi and jaan-pehchaan/jan-pehchan) and later formal (in the form of bureaucratic followed by proprietary) networks to make sense of the changes and uncertainties in turbulent environments. The authors also demonstrate the cyclical nature of strategic sensemaking in the process of developing organizational networks for performance.

The study has a number of theoretical and practical contributions. First, it extends the well-established business networking construct to a more inclusive organizational networking construct. Second, it demonstrates that sensemaking is dependent on interorganizational networking from the outset and throughout the growth of an organization in turbulent markets – from informal to formal bureaucratic and proprietary networks. Finally, this study is unique in documenting the entire process of sensemaking from scanning to performance as well as successfully demonstrating the cyclical nature of sensemaking.

Takaful is a social security approach that guarantees business risks in light of shari’ah, thus playing a crucial role in human life and the economy. The purpose of this study is to examine the factors that influence the behavioural intention of micro, small and medium-sized enterprises (MSMEs) entrepreneurs to participate in takaful in Sri Lanka.

This study is designed quantitatively with deductive approach using the theory of planned behaviour. A total of 432 MSMEs in Sri Lanka were surveyed using convenience sampling to measure the intention to participate in takaful as a risk mitigation. The collected data were analysed through partial least square-structural equational modelling.

Attitude, subjective norm and perceived behavioural control variables positively influenced the intention, with t-values of 3.216, 3.813 and 3.859, respectively. The influence of these variables exhibits not much difference.

This study only focuses on MSMEs and a general takaful scheme. Future researchers may consider family takaful involvement among Sri Lankan business entrepreneurs.

Takaful practitioners should gain from the entrepreneurs’ intention to participate in takaful. Findings from this study could help marketing managers to revamp their strategies to further attract the entrepreneurs and make them to understand risk they are facing and, subsequently, participate in the takaful scheme.

This paper focuses on the context of Muslim minority among pluralism, where there is no regulation for Islamic financial products and services, and under the Islamic financial market crisis. This unleashes how business owners feel about takaful system on different dimensions.

The primary goal of this review is to identify emerging themes in the cold supply chain (CSC) and their future research directions, methodologies, and theories.

The review looks at CSC related articles from Scopus database published in the years 2000–2020. Thereafter, bibliometric and co-citation analyses have been conducted to identify emerging themes, methodologies, and theoretical perspectives related to CSC management.

This study revealed a clear research gap in CSC literature with emerging themes relevant to diverse aspects. Primarily, the most prominent authors, methodologies, and theories were identified from bibliometric analysis. Next, we generated clusters to identify the insights of each cluster using co-citation analysis. Consequently, the significance of clusters concerning the number of articles, theoretical frameworks, methodologies, and themes was recognized. Finally, a few future research questions regarding emerging themes have been identified.

The importance of co-citation and bibliometric analyses in studying the evolution of research over a definite time is emphasized in this work. As per emerging themes, implementing digital technologies has increased the efficiency of traditional CSC and transformed it into digital CSC.

As per the authors' knowledge, this work is the first in literature to explore the significance of identifying emerging areas and future research directions in managing CSC through literature review based on bibliometric and co-citation analysis.

Buoyed by the increasing demand for improved productivity and environmentally conscious manufacturing, research in the area of lean production and green manufacturing has experienced significant growth since Dües et al. (2013). Taking the latter as the point of reference, a review of recent developments in the complementary and conflicting areas between lean production and green manufacturing that has been missing is presented.

A systematic search was done to identify articles on lean production and green manufacturing from Scopus, Web of Science and Google Scholar. The population-intervention-outcome format was used to develop and answer the research questions. ATLAS.ti 22 was used to analyse 141 qualifying papers and identify the research themes.

Lean production and green manufacturing have strong synergy, and when integrated, they tend to deliver superior organisational performance than their individual implementations. This is consistent with the pre-2013 results, and other areas of synergy and divergence were also identified.

The study considers only papers published in the manufacturing sector after Dües et al. (2013). A review of lean production and green manufacturing in integrated product-service systems may also be relevant, especially due to the continuing trend since its introduction.

Any new adopter of lean production should consider implementing it simultaneously with green manufacturing.

This study establishes the persistence of the pre-2013 patterns of synergy and divergence between lean production and green manufacturing, and identifies new considerations for their joint implementation.

Over the last two decades, green supply chain management (GSCM) has enabled businesses to operate in an environmentally friendly manner. The present review examines 234 research articles and proposes a methodical literature review on GSCM, focusing on the aspects of sustainable development.

The work examines conceptual, analytical, empirical and non-empirical research articles, analyzing at all levels of the organization, such as firm, dyad, supply chain and network. The objective of the review is to provide insights into the state and scope of existing research in the domain of GSCM, to identify the prevalence of GSCM and to consolidate the trend of future research. The literature review follows a systematic methodology for analyzing the literature.

The findings can support researchers in identifying research areas with significant impact and streamline research on GSCM in the future. Practitioners can utilize this structured classification to strategize their green initiatives in their firms.

The work contributes to providing literature that explores a detailed review in GSCM. The proposed literature review captures critical aspects in the domain of GSCM and offers future research directions.

Inefficiency dilemmas in project governance are caused by various risks arising from the characteristic of construction supply chain projects, such as poor project performance, conflicts between stakeholders and cost overrun. This research aims to establish a fuzzy synthetic evaluation (FSE) model to analyze construction supply chain risk factors. Corresponding risk mitigation strategies are provided to facilitate the improvement performance of ongoing construction supply chain projects.

A literature review is utilized to reveal the deficiencies of construction supply chain risk management. Thus, a total of five hundred (500) questionnaires are distributed to construction professionals, and four hundred and thirty-five (435) questionnaires are recovered to obtain the evaluation data of construction professionals on critical risk factors. Additionally, the FSE is used to analyze and rank the significance of critical risk factors. Finally, this research discusses nine critical risk factors with high weight in the model, and explains the reason for the significance of critical risk factors in the construction supply chain.

The questionnaire results show that the thirty-one (31) identified critical risk factors are verified by related practitioners (government departments, universities and research institutions, owners, construction units, financial institutions, design units, consulting firms). Thirty-one (31) identified critical risk factors are divided into common risks, risks from contractors and risks from owners. The most significant factors in the three categories, respectively, are “political risks,” “owner's unprofessional” approach and “cash flow.” Managing these risks can facilitate the development of the construction supply chain.

This paper expands the research perspective of construction supply chain risk management and complements the risks in the construction supply chain. For practitioners, the research result provides some corresponding measures to deal with these risks. For researchers, the research result provides the direction of construction supply chain risk treatment.

The development of circular construction supply chains (CCSCs) is impeded by various barriers, but the current literature overlooks the interrelationships among these barriers and the varying nature of associated countermeasures with the growth of circular economy (CE). This paper aims to develop new perspectives about the transition to CCSCs through the lens of supply-push (SP)/demand-pull (DP) strategies and related underpinning theories.

A systematic literature review including 136 journal articles was undertaken to identify barriers to CCSCs and associated countermeasures that are analysed for their relevance to SP/DP. The interplay between SP/DP approaches was discussed using the “technology acceptance” and “innovation chain” models.

(1) Thirty-five barriers were identified and organised into nine main barrier factors; (2) the predominant factors are knowledge and awareness, policy and regulations, technological capabilities, and incentives; (3) CCSCs transition is SP-configured primarily driven by actors above the project network; (4) “push” measures are devised to gradually create a “pull” environment and can be revoked when demand for circularity is created, suggesting a new “push-to-pull” perspective of CCSCs; and (5) a complex adaptative system is witnessed in relationships between barriers and countermeasures, and interactions among actors at all levels.

The findings offer practitioners countermeasures to barriers encountered in CE initiatives. It also informs policymakers of adjusting policies to accommodate the SP-DP movement in steering the circular transition.

This study uses theoretical models to interpret the dynamics in CCSCs transition and proposes a new definition of CCSCs highlighting their complex and dual transitional/transformational nature.

This study aims to describe the fundamentals of teaching risk management in a classroom setting, with an emphasis on the learning interface between higher education and the workplace environment for business management students.

The study reviews literature that uses spreadsheets to visualize and model risk and uncertainty. Using six distinct case-based activities (CBAs), the study illustrates the practical applications of software like Palisade @RISK in risk management education. It helps to close the gap between theory and practice. The software assists in estimating the likelihood of a risk event and the impact or repercussions it will have if it occurs. This technique of risk analysis makes it possible to identify the risks that need the most active control.

@RISK can be used to create models that produce results to demonstrate every potential scenario outcome. When faced with a choice or analysis that involves uncertainty, @RISK can be utilized to enhance the perspective of what the future might contain.

The insights from this study can be used to develop critical thinking, independent thinking, problem-solving and other important skills in learners. Further, educators can apply Bloom’s taxonomy and the problem-solving taxonomy to help students make informed decisions in risky situations.

Grounded in the stakeholder theory and signaling theory, this study aims to broaden the research agenda on environmental, social and governance (ESG) investing by uncovering public sentiments and key themes using Twitter data spanning from 2009 to 2022.

Using various machine learning models for text tonality analysis and topic modeling, this research scrutinizes 1,842,985 Twitter texts to extract prevalent ESG investing trends and gauge their sentiment.

Gibbs Sampling Dirichlet Multinomial Mixture emerges as the optimal topic modeling method, unveiling significant topics such as “Physical risk of climate change,” “Employee Health, Safety and well-being” and “Water management and Scarcity.” RoBERTa, an attention-based model, outperforms other machine learning models in sentiment analysis, revealing a predominantly positive shift in public sentiment toward ESG investing over the past five years.

This study establishes a framework for sentiment analysis and topic modeling on alternative data, offering a foundation for future research. Prospective studies can enhance insights by incorporating data from additional social media platforms like LinkedIn and Facebook.

Leveraging unstructured data on ESG from platforms like Twitter provides a novel avenue to capture company-related information, supplementing traditional self-reported sustainability disclosures. This approach opens new possibilities for understanding a company’s ESG standing.

By shedding light on public perceptions of ESG investing, this research uncovers influential factors that often elude traditional corporate reporting. The findings empower both investors and the general public, aiding managers in refining ESG and management strategies.

This study marks a groundbreaking contribution to scholarly exploration, to the best of the authors’ knowledge, by being the first to analyze unstructured Twitter data in the context of ESG investing, offering unique insights and advancing the understanding of this emerging field.