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Uzbekistan, a former Soviet Union state whose population is 96% Muslim, is aiming to penetrate the global halal market. Since 2016, its government has been committed to establishing a halal economy, purportedly comprising halal product exports and inbound halal tourism services. Given that a conducive halal ecosystem is a critical condition for creating and sustaining a viable halal economy, the current condition of the halal industry in the country must be diagnosed. For this purpose, we developed a diagnostic framework based on the halal principles and the Viable System Model (VSM) to identify the existing players and stakeholders in the halal industry ecosystem in Uzbekistan and their respective roles and functions, as well as the information flows amongst them.

The study utilised the qualitative methodology with the data gathered mainly from in-depth interviews with industry experts and consumers in Uzbekistan.

The findings revealed that the country has considerable potential to develop its halal tourism market due to its beautiful landscape, rich history and cultural heritage, which is supported by a full-fledged development policy. Uzbekistan's industrial sector exhibits substantial readiness to serve the Muslim market; however, the country lacks a specific policy for the development of the halal manufacturing export industry.

Our findings generate emergent themes that are relevant to the operations and future viability of halal industry of a Muslim country in a transitioning economy. These emerging themes further strengthened existing conceptualisation of the Viable System Model in terms of the elements of the environment and the function of policymaking in contributing toward a system's viability. Implications of the findings and suggestions for future research are also provided.

Despite being a seminal explanation of the workforce emotional experiences, capable of mapping the path from the antecedents to consequences, affective events theory (AET) only offers a “macrostructure” of a working environment. To date, little is known about the universal features of the work environment that may guide the understanding of imperative work aspects triggering employees’ emotions at work. Hence, the study proposes and validates that Stafford Beer’s viable system model (VSM) can provide a holistic view of the organizational work environment, enabling a comprehensive understanding of work events or factors triggering workforce emotions.

First, the VSM structural layout is used to fill in the “macrostructure” of the “working environment” in AET to diagnose the functional and relational aspects of the work and the related work events occurring within. Using a deductive approach, 31 work events were adopted to determine the impact of VSM-based work environment events on the employees’ emotional experiences and subsequent work attitudes (job satisfaction) and behaviors (citizenship behavior). To field test the proposed nexus of VSM and AET, the survey was conducted on two hundred and fifteen employees from 39 different organizations. PLS-SEM tested the explanatory power of the suggested VSM’s systemic approach for understanding the affective work environment in totality.

The findings confirmed that the VSM metalanguage provides a holistic view of the organizational functioning and social connectivity disposing of affective work events, helpful in assessing their aggregate influence on employees’ emotions and work-related outcomes.

The findings identify how employees' emotions can be triggered by everyday work operations and social relations at work, which can affect their extra-role behaviors and necessary work-related attitudes.

The study utilized Beer’s VSM framework based on the systemic principle of “holistic view” for ascertaining the affective work environment and its related features holistically, which filled in well the macrostructure of “work environment features” with micro-structures of organizational inter-related aspects which are yet to be known in AET – a seminal explanation for managing workforce emotions.

Artificial intelligence (AI) reasoning is fuelled by high-quality, detailed behavioural data. These can usually be obtained by the biometrical sensors embedded in smart devices. The currently used data collecting approach, where data ownership and property rights are taken by the data scientists, designers of a device or a related application, delivers multiple ethical, sociological and governance concerns. In this paper, the author is opening a systemic examination of a data sharing concept in which data producers execute their data property rights.

Since data sharing concept delivers a substantially different alternative, it needs to be thoroughly examined from multiple perspectives, among them: the ethical, social and feasibility. At this stage, theoretical examination modes in the form of literature analysis and mental model development are being performed.

Data sharing concepts, framework, mechanisms and swift viability are examined. The author determined that data sharing could lead to virtuous data science by augmenting data producers' capacity to govern their data and regulators' capacity to interact in the process. Truly interdisciplinary research is proposed to follow up on this research.

Since the research proposal is theoretical, the proposal may not provide direct applicative value but is largely focussed on fuelling the research directions.

For the researchers, data sharing concepts will provide an alternative approach and help resolve multiple ethical considerations related to the internet of things (IoT) data collecting approach. For the practitioners in data science, it will provide numerous new challenges, such as distributed data storing, distributed data analysis and intelligent data sharing protocols.

Data sharing may post significant implications in research and development. Since ethical, legislative moral and trust-related issues are managed in the negotiation process, data can be shared freely, which in a practical sense expands the data pool for virtuous research in social sciences.

The paper opens new research directions of data sharing concepts and space for a new field of research.

This paper aims to recall the attention on a key challenge for customer relationship management related to the role of human agents in the management of the “switch point” for ensuring the effectiveness and efficiency in a customer-machine conversation.

This study contributes to the discussion about the firms’ approach to artificial intelligence (AI) in frontline interactions under the conceptual umbrella provided by knowledge management studies.

This paper provides a theoretical model for clarifying the role of human intelligence (HI) in AI-based frontline interactions by highlighting the relevance of the actors’ subjectivity in the dynamics and perceptions of customer-machine conversations.

An AI-HI complementarity matrix is proposed in spite of the still dominant replacement view.

The paper aims to enrich current debate about human–technology dichotomy in socio-economic settings by decoding and systematizing the main phases through which it has been approached in managerial and social studies.

A multi-interpretative framework is built thanks to the adoption of a qualitative approach inspired by the inductive logic, and for analyzing the historical evolution of the approach to human–technology dichotomy and for explaining them through an innovative conceptual model.

An innovative conceptual model is proposed for depicting connections and evolutions among the main four phases in the evolution of the approaches to human–technology dichotomy.

Reflections and conceptual model herein can support researchers in rereading the multiple theoretical and practical contributions provided with reference to human and technology relations in socio-economic settings.

The paper can support managers and entrepreneurs in defining and evaluating managerial approaches for efficiently enhancing human–technology interaction.

The paper proposes an innovative conceptual model based on a multi-interpretative framework for decoding the historical evolution of the approaches to human–technology dichotomy in business settings. New variables are added to the current debate about the topic for building an original interpretive viewpoint.

Commercial banks face several risks, including credit, liquidity, operational and disruptive risks. In addition to these risks that are challenging for banks to control and manage, crises and disasters can exert substantially more destructive shocks. These shocks can exacerbate internal risks and cause severe damage to the bank's performance, leading banks to bankruptcy and closure. This study aims to facilitate achieving resilient banking policies through a model-based assessment of business continuity management (BCM) policies.

By applying a system dynamics (SD) methodology, a systemic model that includes a causal structure of the banking business is presented. To build a simulation model, data are collected from a commercial bank in Iran. By presenting the simulation model of the bank's business, the consequences of some given crises on the bank's performance are tested, and the effectiveness of risk and crisis management policies is evaluated. Vensim Personal Learning Edition (PLE) software is used to construct the simulation model.

Results indicate that the current BCM policies do not show appropriate resilience in the face of various crises. Commercial banks cannot create sustainable value for the banks' shareholders despite the possibility of profitability, as the shareholders lack adequate resilience and soundness. These commercial banks do not have the appropriate resilience for the next pandemic after coronavirus disease 2019 (COVID-19). Moreover, the robustness of the current banking business model is very fragile for the banking run crisis.

A forward-looking view of resilient banking can be obtained by combining liquidity coverage, stable funding, capital adequacy and insights from stress tests. Resilient banking requires a balanced combination of robustness, soundness and profitability.

The present study is a combination of bank business management, risk and resilience management and SD simulation. This approach can analyze and simulate the dynamics of bank resilience. Additionally, present of a decision support system (DSS) to analyze and simulate the outcomes of different crisis management policies and solutions is an innovative approach to developing effective and resilient banking policies.

The present paper aims at understanding how horizontal network collaborations between small and medium enterprises (SMEs) can be designed and implemented to take advantage of a supply chain finance (SCF) perspective.

This study presents an SCF literature background identifying four literature gaps, and in response to them it adopts an action research approach. The empirical analysis is developed on a network-case study: a horizontal collaboration project between small businesses of the Italian wine industry and their supply chains.

SMEs can play an active role in developing – in terms of design and implementation – their collaborative networks by taking advantage of an SCF perspective for themselves, and their customers, based on the reorganization of relationships interface processes. Taking this perspective can be a concrete and crucial way to sustain the development of SMEs and their supply chains in an actual competitive context.

The paper identifies the theoretical gaps in the literature, suggests new research areas that deserve to be more deeply investigated and connects case-related results to the key concepts. The empirical part presents a real case application that proposes a complete roadmap for managers and practitioners who wish to experience similar projects.

This network-case study storyline, presenting an overview of ten years of meetings, with related purposes, is suggesting a roadmap for design and implementation of horizontal network as managerial implications. These kinds of active research projects, with a collaborative mixed team of academics and practitioners, and involving a multilayer group of participants, are positive examples for closing the bridge between companies and academia, which enhance this network of small businesses active in trying to improve their competitiveness working together.

The value of the paper is to embrace a supply chain-oriented perspective for an SME, independent of the financial system and based on inventory flow management. Very little literature focuses on inventory-based research within the SCF framework, designed for real implementation in horizontal network collaboration by entrepreneurial ventures.

Business models (BMs) are becoming increasingly crucial for value creation in the healthcare sector. The study explores the conceptualization and application of BM concepts within the healthcare sector and investigates their evolution in emerging economies (EEs) and developed economies (DEs). This study aims to uncover these two contexts' shared characteristics and unique variances through a comparative analysis.

The paper systematically investigates and consolidates the literature on healthcare by employing the antecedents, decisions and outcomes (ADO) framework and finally examines 71 shortlisted articles published between 2003 and 2022.

The recognition of the BM within healthcare is increasing, both in EEs and DEs. EEs prioritize value creation and capture through cost efficiency, while DEs focus on innovation. Key theories employed include a resource-based view, the network theory and the theory of innovation. Case studies are commonly used as a methodology. Further research is needed to explore the decisions and outcomes of BMs.

The study adopts stringent filtration and keyword criteria, potentially excluding relevant research. Future researchers are encouraged to broaden their selection criteria to encompass a more extensive range of relevant studies.

Beyond comparing and highlighting gaps in BMs between EEs and DEs, benchmarking DE's healthcare business models (HBMs) helps healthcare organizations in EEs align their practices, mitigate risks and establish efficient healthcare systems tailored to their specific contexts. The study adopts stringent filtration and keyword criteria, potentially excluding relevant research. Future researchers are encouraged to broaden their selection criteria to encompass a more extensive range of relevant studies.

The study analyzes HBMs using an SLR framework perspective and provides practical implications for academicians and practitioners to enhance their decision-making.

This study aims to create a system dynamics simulation model to forecast the performance of small and medium-sized enterprises (SMEs) if some decision-making is executed to reduce the negative of the coronavirus disease 2019 (COVID-19) pandemic. In particular, this study will focus on SMEs that belong to the furniture industry because the furniture industry is one of the leading industries in Indonesia.

The study develops a system dynamics-based model by using three subsystems, i.e. the “production subsystem,” “demand and revenue subsystem” and “raw material (or wood supply) subsystem.”

The best scenario is the third scenario which increases the capacity to the normal situation and government subsidy during and after the pandemic. This scenario gives the best performance for industry revenue and gross domestic product (GDP). However, for the government, the most significant expenditure occurs in the third scenario. This seems a trade-off for the government whether to save the wooden-based furniture industry by encouraging the industry to continue operating during the pandemic accompanied by high subsidies or limiting the activities of the wooden-based furniture industry to prevent the spread of COVID-19 by providing low subsidies.

First, this study does not try to combine the system dynamics (SD) methodology with the other method or use a multi-methodology since SD has several limitations and the other method may have several advantages compared to SD. Second, the models used in this study do not consider the decline in forest area and quality. Third, the demand for wooden-based furniture is obtained from historical data on domestic and foreign sales and fourth, the model does not include the government budget as a constraint to make any subsidy to help the SMEs.

This study provides essential insights into implementing the policies in the world pandemic situation when SMEs face lockdown policy.

The study revealed that relevant policy scenarios could be built after simulating and analyzing each scenario's effect on SMEs' performance during the pandemic.

This study will enrich the previous study on the impact of the pandemic on SMEs and the dynamic system modeling on SMEs. The previous study discussed the pandemic's impact on SME performance and the impact's analysis in isolation from the dynamic nature of SME owners' decisions or government policy. In this study, the impact generated from the pandemic situation could be different depending on the decision and policies taken by managers from SMEs and the government.

The purpose of this paper is to examine how holistic thinking and the use of systems methodologies can help organisations handle increased problem complexity. The paper provides a critical discussion of the development of applied systems thinking and examines how its main strands can deal with problem complexity, multiple perceptions of reality and the unequal access to power resources in organisations.

The paper uses social theory and a systems meta-theoretical framework to examine the different ontological and epistemological assumptions that each strand of applied systems thinking makes about the nature of problems and the way in which an intervention will be made.

Complex problems require joined-up thinking and the use of systems ideas. Viewing the problem situation from a holistic perspective and applying appropriate systems methodologies and tools can help managers handle the complexities that their organisations face.

The paper makes a clear link between systems approaches and social theory and emphasises the need to understand the different assumptions that theories, methodologies or people make when they intervene in complex problem situations.