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The rising number of food recalls has raised concerns about complexity, globalization and weak governance in the food supply chain. This paper aims to investigate the recall of plant-based products with data from the US Food and Drug Administration.

Introducing the structural topic modeling method allowed us to test theories on recall in the context of sustainable food consumption, enhancing the understanding of food recall processes. This approach helps identify latent topics of product recalls and their interwoven relationships with various stakeholders.

The results answer a standing research call for empirical investigation in a nascent food industry to identify stakeholders’ engagements for food safety crisis management for corporate social responsibility practices. This finding provides novel insights on managing threats to food safety at an industry level to extend existing antecedents and consequences of product recall at a micro level.

For practitioners, this empirical finding may provide insights into stakeholder management and develop evidence-based strategies to prevent threats to food safety. For public policymakers, this analysis may help identify patterns of recalls and assist guidelines and alarm systems (e.g. EU’s Rapid Alert System for Food and Feed) on threats in the food supply chain.

Two detected clusters, such as opportunisms of market actors in the plant-based food system and food culture, from the analysis help understand corporate social responsibility and food safety in the plant-based food industry.

The purpose of this paper is to develop a software-library in the R programming language that implements the concepts of the interpretive coordinate, interpretive axis and interpretive plane. This allows for the automatic and reliable interpretation of results from the multiple correspondence analysis (MCA) as previously proposed and published. Consequently, the users can seamlessly apply these concepts to their data, both via R commands and a corresponding graphical interface.

Within the context of this study, and through extensive literature review, the advantages of developing software using the Shiny library were examined. This library allows for the development of full-stack applications for R users without the need for knowledge of the corresponding technologies required for the development of complex applications. Additionally, the structural components of a Shiny application were presented, leading ultimately to the proposed software application.

Software utilizing the Shiny library enables nonexpert developers to rapidly develop specialized applications, either to present or to assist in the understanding of objects or concepts that are scientifically intriguing and complex. Specifically, with this proposed application, the users can promptly and effectively apply the scientific concepts addressed in this study to their data. Additionally, they can dynamically generate charts and reports that are readily available for download and sharing.

The proposed package is an implementation of the fundamental concepts of the exploratory MCA method. In the next step, discoveries from the geometric data analysis will be added as features to provide more comprehensive information to the users.

The practical implications of this work include the dissemination of the method’s use to a broader audience. Additionally, the decision to implement it with open-source code will result in the integration of the package’s functions by other third-party user packages.

The proposed software introduces the initial implementation of concepts such as interpretive coordination, the interpretive axis and the interpretive plane. This package aims to broaden and simplify the application of these concepts to benefit stakeholders in scientific research. The software can be accessed for free in a code repository, the link to which is provided in the full text of the study.

The purpose of this paper is to create an automatic interpretation of the results of the method of multiple correspondence analysis (MCA) for categorical variables, so that the nonexpert user can immediately and safely interpret the results, which concern, as the authors know, the categories of variables that strongly interact and determine the trends of the subject under investigation.

This study is a novel theoretical approach to interpreting the results of the MCA method. The classical interpretation of MCA results is based on three indicators: the projection (F) of the category points of the variables in factorial axes, the point contribution to axis creation (CTR) and the correlation (COR) of a point with an axis. The synthetic use of the aforementioned indicators is arduous, particularly for nonexpert users, and frequently results in misinterpretations. The current study has achieved a synthesis of the aforementioned indicators, so that the interpretation of the results is based on a new indicator, as correspondingly on an index, the well-known method principal component analysis (PCA) for continuous variables is based.

Two (2) concepts were proposed in the new theoretical approach. The interpretative axis corresponding to the classical factorial axis and the interpretative plane corresponding to the factorial plane that as it will be seen offer clear and safe interpretative results in MCA.

It is obvious that in the development of the proposed automatic interpretation of the MCA results, the authors do not have in the interpretative axes the actual projections of the points as is the case in the original factorial axes, but this is not of interest to the simple user who is only interested in being able to distinguish the categories of variables that determine the interpretation of the most pronounced trends of the phenomenon being examined.

The results of this research can have positive implications for the dissemination of MCA as a method and its use as an integrated exploratory data analysis approach.

Interpreting the MCA results presents difficulties for the nonexpert user and sometimes lead to misinterpretations. The interpretative difficulty persists in the MCA's other interpretative proposals. The proposed method of interpreting the MCA results clearly and accurately allows for the interpretation of its results and thus contributes to the dissemination of the MCA as an integrated method of categorical data analysis and exploration.

The housing policies targeting low-income households have not been effective to address the housing needs of target groups in Iran over the past four decades. According to the World Bank’s data on population living in slums (% of urban population) in Iran in 2018 was 25% which is slightly higher than the rate 23% of upper-middle-income countries. This study aims to understand what major revisions are required in the process of housing policymaking to have more effective policies.

The authors conduct one-to-one interviews with 41 housing experts and apply discourse analysis and interpretive–structural modeling to achieve the goals.

The panel of experts argue that the success of housing policies in Iran depends on the following: all academic disciplines should be included in the process of housing policymaking process; land policymaking should be modified; housing policy is a regional issue, and it should be designed and implemented differently in each province; main modifications are required in the tax and tenancy system; and new policies are required to push vacant houses into the rental market.

This study is a prescriptive study based on a general trend (four decades).

In the context of promoting sustainable development in SMEs, the present study aims to investigate the relationship among solution dimensions based on the Industry 4.0 (I4.0) concept.

The study employs a comprehensive methodology that includes a systematic literature review, workshop, grounded theory and interpretive structural modeling. Various dimensions concerning I4.0 sustainability are tested and evaluated using a questionnaire design followed by hypothesis formulation. Further, grounded theory is used to extract the key solution dimensions that capture the essence of I4.0 implementation in SMEs. Finally, the solution dimensions for I4.0 sustainability are modeled using the ISM approach to understand the structural interdependencies among them, and Matrice d'Impacts Croisés Multiplication Applied to a Classification (MICMAC) analysis is done to understand the driving and dependence power among these dimensions.

The study identified 14 solution dimensions for the implementation of I4.0 in SMEs for sustainable development. Out of the 14 solution dimensions, human resource training programs (D4) appear at level 11, followed by top management commitment (D1), strategic collaborations (D3) and coordination among key stakeholders (D5) at level 2 in the hierarchical interpretive structural modeling (ISM) model. Also, these dimensions have an effect size of more than 0.50 which indicates a substantial correlation between the sustainability dimensions and Industry 4.0 implementation in SMEs.

The study contributes to the overall goal of fostering sustainability within the SME sector, which can pave the way for various stakeholders for the successful implementation of I4.0 sustainable solution dimensions.

While the potential for digital innovation (DI) to transform organizational practices is widely acknowledged in the information systems (IS) literature, there is very limited understanding on the socio-political nature of institutional interactions that determine DI and affect organizational practices in social cash organizations. Drawing on the neo-institutionalist vision, the purpose of the study is to examine the unique set of institutional exchanges that influence the transition to digital social cash payments that give rise to new institutional arrangements in social cash organizations.

The paper draws on an in-depth case study of a government social cash organization in Pakistan. Qualitative data were collected using 30 semi-structured interviews from key organizational members and stakeholders.

The results suggest that DI is determined by the novel intersections between the coercive (techno-economic, regulatory), normative (socio-organizational), mimetic (international) and covert power (political) forces. Hence, DI is not a technologically deterministic output, but rather a complex socio-political process enacted through dialogue, negotiation and conflict between institutional actors. Technology is socially embedded through the process of institutionalization that is coupled by the deinstitutionalization of established organizational practices for progressive transformation.

The research has implications for government social cash organizations especially in the Global South. Empirically, the authors gained rare access to, and support from a government-backed social cash organization in Pakistan (an understudied country in the Global South), which made the data and the consequent analyses even invaluable. This made the empirical contribution within this geographical setting even more worthy, since this case study has received little attention from indigenous scholars in the past. The empirical findings showcased a unique set of contextual factors that were subject to BISP and interpreted through an account of socio-cultural sensitivities.

The paper provides practical implications for policymakers and practitioners, emphasizing the need to address institutional challenges, including covert power, during the implementation of digitalization projects in the public sector. The paper has certain potential for inspiring future e-government related (or public sector focused) studies. The paper may guide both private and government policy-makers and practitioners in presenting how to overcome certain institutional challenges while planning and implementing large scale multi-stakeholder digitization projects in similar country contexts. So while there is scope of linking the digitization of public sector organizations to anti-corruption measures in other Global South countries, the paper may not be that straightforward with the private sector involvement.

The paper offers rich social insights on the institutional interchanges that occur between the social actors for the innovation of technology. Especially, the paper highlights the social-embeddedness nature of technology that underpins the institutionalization of new organizational practices. These have implications on how DI is viewed as a socio-political process of change.

This study contributes to neo-institutional theory by theorizing covert power as a political force that complements the neo-institutional framework. This force is subtle but also resistive for some political actors as the force shifts the equilibrium of power between different institutional actors. Furthermore, the paper presents the social and practical implications that guide policymakers and practitioners by taking into consideration the unique institutional challenges, such as covert power, while implementing large scale digital projects in the social cash sector.

This paper aims to contribute to the ongoing methodological discussions surrounding the adoption of ethnographic approaches in accounting by undertaking a comparative analysis of ethnography in anthropology and ethnography in qualitative accounting research. By doing so, it abductively speculates on the factors influencing the distinct characteristics of ethnography in accounting and explores their implications.

This paper uses a comparative approach, organizing the comparison using Van Maanen’s (2011a, 2011b) framework of field-, head- and text-work phases in ethnography. Furthermore, it draws on the author’s experience as a qualitative researcher who has conducted ethnographic research for more than a decade across the disciplines of anthropology and accounting, as well as for non-academic organizations, to provide illustrative examples for the comparison.

This paper finds that ethnography in accounting, when compared to its counterpart in anthropology, demonstrates a stronger inclination towards scientific aspirations. This is evidenced by its prevalence of realist tales, a high emphasis on “methodological rigour”, a focus on high-level theorization and other similar characteristics. Furthermore, the scientific aspiration and hegemony of the positivist paradigm in accounting research, when leading to a change of the evaluation criteria of non-positivist research, generate an impoverishment of interpretive and ethnographic research in accounting.

This paper provides critical insights from a comparative perspective, highlighting the marginalized position of ethnography in accounting research. By understanding the mechanisms of marginalization, the paper commits to reflexivity and advocates for meaningful changes within the field.

The aim of the paper is to rank and analyze the key strategies to sustainable finance adoption in the manufacturing sector using Fuzzy Delphi method (FDM), Interpretive Structural Modeling (ISM) and MICMAC (impact matrix cross-reference multiplication applied to a classification) analysis.

The study develops a novel framework to identify and analyze the mutual relationships among set of sustainable policies using extensive literature survey and experts opinion. Initially, the study found 14 strategies to implement sustainable finance with the help of vast literature. Then, the list of identified factors were screened through Fuzzy Delphi Method (FDM). Based on driving and dependence power, the final list of factors are divided into three categories.

The study findings reveal that “environmental rules and practices”, “financial incentives, tax reduction and subsidy”, have strongest driving power for promoting sustainable financial system in Pakistani manufacturing sector. Furthermore, “environmental awareness” and “long term vision” are found to be highly influenced by other corresponding elements in a system.

The ISM approach assists professionals, academics, and managers in identifying and ranking policies in implementing green business techniques. The hierarchical representation of ISM results provides a roadmap for decision-makers to navigate and prioritize factors effectively, facilitating the implementation of strategies that contribute to sustainable growth within organizations.

The study results provide interesting clues regarding green finance policies that provide the foundations, incentives, protections or other provisions that support the ecological conservancy’s mission. Specifically, the findings guide that government must offer research grants to private enterprises, research and development institutions, and universities to promote environmental protection and develop transformative technologies such as waste recycling, renewable energy, carbon capture, and power consumption.

The exploration of strategies for sustainable finance adoption with the help of mixed methodological approach and classification of these strategies on the basis of importance level is a new attempt in the field of manufacturing sector.

This research aims to ascertain the various operational maturity challenges faced by the online food ordering and delivery enterprises (OFODE), their nature and their interactive relationships. In particular, this paper aims to (a) identify the most relevant operational maturity challenges faced by the OFODE during the COVID-19 lockdown in Oman, (b) explore and establish any likely structural relationship among these challenges and (c) put them into logical clusters.

Experts helped to reduce the 18 initially identified maturity challenges to 13 most pressing ones. Mutual relationships, dominance of interactions and their classifications were explored using fuzzy interpretive structural modeling (FISM) and fuzzy MICMAC analysis.

The study of situation-specific operational maturity challenges convinced the authors to propose a distinct FISM model that depicts the relationship among these challenges. Keeping commissions and fees reasonable emerges as the challenge which all other challenges seemingly culminate into. One of the most important situation-specific challenges (i.e. customer confidence about infection free delivery) emerges as a linkage challenge which aggravates as well as is aggravated by certain challenges.

Besides enriching literature, the proposed model has implications for practitioners particularly when the similar lethal waves are experienced anywhere. The number of respondents, subjective approach, specific context as well as the geographical area coverage are the key limitations.

To the best of the authors’ knowledge, this study is the first known scientific effort which attempts to model the operational maturity challenges faced by the OFODE during COVID-19 lockdown period. The authors used the FISM modeling approach to forge these interrelated challenges into a structural model.

Globally, hepatitis C treatment uptake is lower among people who are homeless or unstably housed compared to those who are housed. Understanding and addressing this is essential to ensure no one is left behind in hepatitis C elimination efforts. This study aims to explore peoples’ experiences of unstable housing and health care, and how these experiences influenced engagement in hepatitis C treatment.

Purposive sampling was used to recruit people with lived experience of injection drug use, hepatitis C and unstable housing in Melbourne, Australia. In-depth semistructured interviews were conducted and a case study approach with interpretative phenomenological analysis was used to identify personal experiential themes and group experiential themes.

Four people were interviewed. The precarious nature of housing for women who inject drugs was a group experiential theme, however, this did not appear to be a direct barrier to hepatitis C treatment. Rather, competing priorities, including caregiving, were personal experiential themes and these created barriers to treatment. Another group experiential theme was “right place, right time, right people” with these three elements required to facilitate hepatitis C treatment.

There is limited research providing in-depth insight into how personal experiences with unstable housing and health care shape engagement with hepatitis C treatment. The analyses indicate there is a need to move beyond a “one size fits-all” approach to hepatitis C care. Instead, care should be tailored to the needs of individuals and their personal circumstances and regularly facilitated. This includes giving greater attention to gender in intervention design and evaluation, and research more broadly.