Journal of Modelling in Management最新文献

Purpose

This paper aims to explore the underlying intention behind using blockchain technology (BLCT) in the agri-food supply chain (AFSC). This is achieved by using a conceptual framework based on technology acceptance models that considers various factors influencing user behavior toward implementing this technology in their practices.

Design/methodology/approach

The conceptual framework developed is empirically validated using structural equation modeling (SEM). A total of 258 respondents from agri-food domain in India were involved in this survey, and their responses were analyzed through SEM to validate our conceptual framework.

Findings

The findings state that food safety and security, traceability, transparency and cost highly influence the intention to use BLCT. Decision-makers of the AFSCs are more inclined to embrace BLCT if they perceive the usefulness of the technology as valuable and believe it will enhance their productivity.

Practical implications

This study contributes to the existing literature by providing thorough examination of the variables that influence the intention to adopt BLCT within the AFSC. The insights aim to benefit industry decision-makers, supply chain practitioners and policymakers in their decision-making processes regarding BLCT adoption in the AFSC.

Originality/value

This study investigates how decision-makers’ perceptions of BLCT influence their intention to use it in AFSCs, as well as the impact of the different underlying factors deemed valuable in the adoption process of this technology.

Purpose

This study aims to evaluate the impact of sustainable strategic planning and management (SSPM) on sustainable performance (ecological, social and economic) among micro, small and medium enterprises (MSME) in the culinary sector in Southeast Asia (SEA).

Design/methodology/approach

This study used a quantitative approach surveying 300 halal-certified MSMS culinary businesses in the SEA region. Data were gathered using an online survey platform and analyzed using the partial least squares structural equation modeling technique.

Findings

Green management (GRM), digital transformation management (DTM) and Halal Business Management (HBM) exert a significant influence on SSPM. Furthermore, SSPM positively influences the sampled halal culinary MSMEs’ ecological, social and economic performances in SEA. The study also reveals that GRM, DTM and HBM positively influence Islamic ethics compliance and good governance.

Research limitations/implications

This study sheds light on the often-ignored MSME business in the halal culinary sector in SEA. Examining sustainable and strategic planning synergy strengthens the development of a comprehensive framework for SSPM and could encourage more MSMEs to practice sustainable business operations. Moreover, the research also underlines the urgent need to harmonize halal standards in the SEA region. The approach would intensify multilateral support for economic growth and halal trade between SEA countries and beyond.

Originality/value

This study addresses the research gap in the strategic and sustainable management of halal culinary MSMEs within the developing and vast SEA economic region. This research is among the few, if not the first, that combines the GRM, DTM and HBM influence on SSPM and examines the impact on sustainable, ethical and good governance performances. The insights derived from this study contribute to formulating robust, sustainable policies, fostering avenues for sustainable initiatives and enhancing regional and global cooperation for a sustainable future.

Purpose

The current research has developed a novel method to update the decisions regarding real-time data, named the dynamic adjusted real-time decision-making (DARDEM), for updating the decisions of a grocery supply chain that avoids both frequent modifications of decisions and apathy. The DARDEM method is an integration of unsupervised machine learning and mathematical modeling. This study aims to propose a dynamic proposed a dynamic distribution structure and developed a bi-objective mixed-integer linear program to make distribution decisions along with supplier selection in the supply chain.

Design/methodology/approach

The constantly changing environment of the grocery supply chains shows the necessity for dynamic distribution systems. In addition, new disruptive technologies of Industry 4.0, such as the Internet of Things, provide real-time data availability. Under such conditions, updating decisions has a crucial impact on the continued success of the supply chains. Optimization models have traditionally relied on estimated average input parameters, making it challenging to incorporate real-time data into their framework.

Findings

The proposed dynamic distribution and DARDEM method are studied in an e-grocery supply chain to minimize the total cost and complexity of the supply chain simultaneously. The proposed dynamic structure outperforms traditional distribution structures in a grocery supply chain, particularly when there is higher demand dispersion. The study showed that the DARDEM solution, the online solution, achieved an average difference of 1.54% compared to the offline solution, the optimal solution obtained in the presence of complete information. Moreover, the proposed method reduced the number of changes in downstream and upstream decisions by 30.32% and 40%, respectively, compared to the shortsighted approach.

Originality/value

Introducing a dynamic distribution structure in the supply chain that can effectively manage the challenges posed by real-time demand data, providing a balance between distribution stability and flexibility. The research develops a bi-objective mixed-integer linear program to make distribution decisions and supplier selections in the supply chain simultaneously. This model helps minimize the total cost and complexity of the e-grocery supply chain, providing valuable insights into decision-making processes. Developing a novel method to determine the status of the supply chain and online decision-making in the supply chain based on real-time data, enhancing the adaptability of the system to changing conditions. Implementing and analyzing the proposed MILP model and the developed real-time decision-making method in a case study in a grocery supply chain.

Purpose

This study aims to investigate the combined use of System Dynamics (SD) applications in Enterprise Engineering (EE) research and practice. SD application in EE is becoming widely accepted as a tool to support decision-making processes and for capturing relationships within enterprises.

Design/methodology/approach

A systematic literature review (SLR) is conducted using a standard SLR method to provide a comprehensive review of existing literature. The search was conducted on ten platforms identifying 30 publications which were analysed through the use and development of a codebook.

Findings

The SLR showed that 90% of the result set consisted of peer-reviewed academic conferences and journal papers. The SLR identified a highly dispersed author set of 83 authors. Amongst these authors, Vinay Kulkarni was an active author who has co-authored up to four publications in this research area. The analysis further revealed that the combined use of SD applications and EE is an emerging research area that still needs to develop in maturity. While all phases of EE have received attention, the current research work is more focused on the design phase. The important gap between model development and implementation is identified.

Originality/value

The study elucidates the existing status of interdisciplinary research combining techniques from the SD and EE disciplines, suggesting future research topics that combine the strengths of these existing disciplines.

Purpose

This study aims to identify the factors influencing the creation of a toxic workplace and to examine how to improve a toxic workplace in the electronics industry.

Design/methodology/approach

First, the factors that influence the creation of a toxic work environment were identified by reviewing the research literature. Then, the current status of each identified factor in Iran’s electronics industry was evaluated by developing a questionnaire. Based on the survey data, a relationship map between the factors influencing the toxic workplace was created using the fuzzy cognitive mapping technique. Finally, scenarios were designed to improve the toxic workplace.

Findings

The results show that the “workplace bullying” factor is the factor with the highest centrality in relation to other factors. The results of the scenario design indicate the effectiveness of the “unrealistic expectations at work” factor as a scenario trigger.

Originality/value

This study helps reduce the toxic workplace in the organization, which plays an important role in improving the employees’ work performance and the organization’s development.

Purpose

The purpose of this study is to explore the potential impact of blockchain technology on supply chain performance (SCP). This study further delves into the enablers of blockchain adoption (BA) in SCM and investigates both the direct and mediated effects of blockchain assimilation on garnering a competitive edge in the supply chain and bolstering innovation proficiency, ultimately enhancing SCP.

Design/methodology/approach

This study used a quantitative approach, leveraging partial least squares structural equation modelling. Empirical data were sourced from 500 validated data sets obtained through questionnaires.

Findings

The results indicate that technological readiness and knowledge sharing are key drivers for integrating blockchain into supply chains, with technology readiness displaying a substantially stronger influence. Furthermore, BA significantly enhances supply chain innovation capabilities (SCIC), competitive performance (CP) and overall supply chain efficiency. Notably, both SCIC and CP mediate and amplify the positive effects of blockchain on SCP, emphasising the vital role of innovation and competition in optimising the benefits of blockchain.

Originality/value

To the best of the authors’ knowledge, this study is the first to bridge the gap in the literature connecting SCM and blockchain. The established model augments the theoretical discourse on the SCM-blockchain, offering scholars a validated framework that can be adapted and built upon in future studies.

Purpose

This paper aims to simulate vital corrective actions (CAs) affecting system availability through a system dynamics approach based on the results obtained by analyzing the causal relationships among failure modes and effects analysis elements.

Design/methodology/approach

A stock and flow diagram has been developed to simulate system behaviors during a timeframe. Some improvement scenarios regarding the most necessary CAs according to their strategic priority and the possibility of eliminating root causes of critical failure modes in a roller-transmission system have been simulated and analyzed to choose the most effective one(s) for the system availability. The proposed approach has been examined in a steel-manufacturing company.

Findings

Results indicated the most effective CAs to remove or diminish critical failure causes that led to the less reliability of the system. It illustrated the impacts of the selected CAs on eliminating or decreasing root causes of the critical failure modes, lessening the system’s failure rate and increasing the system availability more effectively.

Research limitations/implications

Results allow managers and decision-makers to consider different maintenance scenarios without wasting time and more cost, choosing the most appropriate option according to system conditions.

Originality/value

This study innovation would be the dynamic analysis of interactions among failure modes, effects and causes over time to predict the system behavior and improve availability by choosing the most effective CAs through improvement scenario simulation via VENSIM software.