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This paper aims to identify, synthesise and critically examine the extant academic research on the relation between big data analytics (BDA), corporate accountability and non-financial disclosure (NFD) across several disciplines.

This paper uses a structured literature review methodology and applies “insight-critique-transformative redefinition” framework to interpret the findings, develop critique and formulate future research directions.

This paper identifies and critically examines 12 research themes across four macro categories. The insights presented in this paper indicate that the nature of the relationship between BDA and accountability depends on whether an organisation considers BDA as a value creation instrument or as a revenue generation source. This paper discusses how NFD can effectively increase corporate accountability for ethical, social and environmental consequences of BDA.

This paper presents the results of a structured literature review exploring the state-of-the-art of academic research on the relation between BDA, NFD and corporate accountability. This paper uses a systematic approach, to provide an exhaustive analysis of the phenomenon with rigorous and reproducible research criteria. This paper also presents a series of actionable insights of how corporate accountability for the use of big data and algorithmic decision-making can be enhanced.

This paper discusses how NFD can reduce negative social and environmental impact stemming from the corporate use of BDA.

To the best of the authors’ knowledge, this paper is the first one to provide a comprehensive synthesis of academic literature, identify research gaps and outline a prospective research agenda on the implications of big data technologies for NFD and corporate accountability along social, environmental and ethical dimensions.

This research aims to examine and understand the rationales and modalities behind the use of disclosure before, during and after a corporate governance scandal involving CPA Australia (CPAA).

Data beyond CPAA's annual reports were collected, such as news articles, media releases, an independent review panel (IRP) report, and the Chief Operating Officer's letter to members. These disclosures were manually coded and analysed through the word counts and word trees in NVivo. This study also relied on Norbert Elias' conceptual tool of power games among networks of actors – figurations – to model the scandal as a power game between the old Board, the press, concerned members, the IRP and the new Board. This study analysed the data to reveal a collective and in fieri power balance that changed with the phases of the scandal.

A mix of voluntary, involuntary, requested and absent disclosures was important in triggering, managing and ending the CPAA scandal. Moreover, communication and disclosure fulfilled a constitutive role since both: mobilised actors, enabled coordination among actors, contributed to pursuing shared goals and influenced power balances. Such a constitutive role was at the heart of the ability of coalitions of figurations to challenge and restore the powerful status quo.

This research introduces to accounting studies the collective and in fieri dimensions of power from figurational theory. Moreover, the research sheds new light on using voluntary, involuntary, requested and absent disclosures before, during and after a corporate crisis.

In this article, we discuss an innovative audience research methodology developed for the AHRC-funded “Beyond the Multiplex: Audiences for Specialised Film in English Regions” project (BtM). The project combines a computational ontology with a mixed-methods approach drawn from both the social sciences and the humanities, enabling research to be conducted both at scale and in depth, producing complex relational analyses of audiences. BtM aims to understand how we might enable a wide range of audiences to participate in a more diverse film culture, and embrace the wealth of films beyond the mainstream in order to optimise the cultural value of engaging with less familiar films. BtM collects data through a three-wave survey of film audience members’ practices, semi-structured interviews and film-elicitation groups with audience members alongside interviews with policy and industry experts, and analyses of key policy and industry documents. Bringing each of these datasets together within our ontology enables us to map relationships between them across a variety of different concerns. For instance, how cultural engagement in general relates to engagement with specialised films; how different audiences access and/or share films across different platforms and venues; how their engagement with those films enables them to make meaning and generate value; and how all of this is shaped by national and regional policy, film industry practices, and the decisions of cultural intermediaries across the fields of film production, distribution and exhibition. Alongside our analyses, the ontology enables us to produce data visualisations and a suite of analytical tools for audience development studies that stakeholders can use, ensuring the research has impact beyond the academy. This paper sets out our methodology for developing the BtM ontology, so that others may adapt it and develop their own ontologies from mixed-methods empirical data in their studies of other knowledge domains.

The purpose of this paper is to set forth a conceptual model describing the actors and roles in ecosystems created to enable productive black entrepreneurship in the USA.

This paper provides a systematic literature review of entrepreneurship ecosystems. It further leverages such literature review by using an autoethnographic approach recommended by Guyotte and Kochacka (2016), drawing on the authors’ practical experience in studying, owning, educating or consulting employer businesses owned by persons of color in the USA and abroad.

Each actor in the ecosystem has practical wisdom and assets that can be shared and leveraged through interacting with the other actors either as role model institutions or capacity development institutions, thus mitigating social inequalities and boosting economic progress by extending entrepreneurial opportunities beyond those that are greatly resourced.

Our literature review is based on selected samples of relevant articles on entrepreneurship ecosystem research and ethnic minority entrepreneurship, and thus, is not exhaustive. The selection was partly influenced by the authors’ opinion of whether a given study was relevant or not to a black entrepreneurship ecosystem. There is the possibility that some relevant studies were excluded. Thus, other actors are encouraged to revise or adapt this model to inform their distinct roles and goals.

The proposed model can help actors involved in the operation or support of a black-owned business make optimal business decisions, enabling each actor to be instrumental in another’s understanding of how to facilitate the success of black American entrepreneurs and business owners and thus, deploy marketing campaigns to boost the visibility and role of each actor. These campaigns play a role in their entrepreneurial marketing efforts.

Responding to Gines and Sampson’s (2020) call, to the best of the authors’ knowledge, this paper is the first to explicitly provide a comprehensive black entrepreneurship ecosystem model that identifies the actors, roles and activities that can help black Americans address social inequalities that limit their ability to become a successful employer business. The proposed model may aid in deepening the theoretical discussion on entrepreneurial ecosystems and be of inspiration for the future works of scholars and practitioners interested in the entrepreneurship and marketing interface.

This study aims to explore how green supply chain management (GSCM) strategies can be effectively implemented for business supply chain operations, relationship management and product design to gain green competitive advantages.

An exploratory in-depth case study was conducted with one of the largest Chinese electronics manufacturers that is considered a leading GSCM adopter in the industry, to understand how the company adopts green supply chain practices across its multiple product lines.

The findings show that businesses can build different green focuses across GSCM elements of green operation, green relationship management and green product design to form diverse hybrid strategic solutions. They include green control, lean, leagile, agile and clean innovation while taking consideration of supply chain type and product lifespan. A taxonomy of four key GSCM strategic combinations is proposed based on the findings. The strategies align with green demand and supply chain characteristics balancing a series of business competitive objectives in terms of reducing pollution and waste, improving green cost efficiency, enhancing green demand innovation and building green service effectiveness.

This study lends insight into the strategic alignment relationships between product supply chain types and approaches to GSCM.

The findings of this study can support industry practitioners in formulating aligned GSCM strategies based on product types to achieve optimal results.

Optimised green supply chain design, operations and relationship management incorporating product attributes can help further minimise negative impacts of business activities on the environment.

This research provides a systematic understanding of how product supply chain types can influence GSCM strategy formulation. It gives a holistic picture of how hybrid choices of strategies with green supply chain operations, relationship management and product design can be formulated based on product and supply chain characteristics.

The purpose of this study is to examine the impact of computer-assisted language learning on cultural adaptation and language learning in non-traditional classroom settings.

The data of this study came from extended periods of observation, multiple rounds of semi-structured interviews and home visits. Using narrative inquiry, it analyzes an immigrant's journey of language learning and cultural adaptation within a virtual knowledge community.

The findings of this study reveal the profound impact of virtual knowledge communities on enhancing second language learning and facilitating cultural adaptation.

This study offers original insights by demonstrating the transformative power of virtual knowledge communities for the purpose of second language acquisition and cultural adaptation.

This study aims to explore the role of frontline service employees’ (FSEs) awareness that their job can be substituted by smart technology, artificial intelligence, robotics and algorithms (STARA) in their job autonomy and proactive service performance and when these relationships can be buffered. Drawing on the cognitive appraisal theory of stress, the study examined the mediating relationship between FSEs’ STARA awareness, job autonomy and proactive service performance and the moderating effects of self-efficacy and resilience on this relationship.

The authors administered two-wave online surveys to 301 South Korean FSEs working in various service sectors (e.g. retailing, food/beverage, hospitality/tourism and banking). The Time 1 survey measured respondents’ STARA awareness, self-efficacy, resilience and job autonomy, and the Time 2 survey assessed their proactive service performance.

FSEs’ STARA awareness negatively affected their subsequent proactive service performance through decreased job autonomy. The negative association between STARA awareness and job autonomy was weaker when FSEs’ self-efficacy was high than when it was low. While the authors observed no significant moderation of resilience, the author found a marginally significant three-way interaction between STARA awareness, self-efficacy and resilience. Specifically, STARA awareness was negatively related to job autonomy only when both self-efficacy and resilience were low. When either self-efficacy or resilience was high, the association between STARA awareness and job autonomy became nonsignificant, suggesting the buffering roles of the two personal resources.

Given that the measurement of variables relied on self-reported data, rater biases might have affected the findings of the study. Moreover, the simultaneous measurement of STARA awareness, self-efficacy, resilience and job autonomy could preclude causal inferences between these variables. The authors encourage future studies to use a more rigorous methodology to reduce rater biases and establish stronger causality between the variables.

Service firms can decrease FSEs’ STARA awareness through training in the knowledge and skills necessary to work with these technologies. To promote FSEs’ proactive service performance in this context, service firms need to involve them in decisions related to STARA adoption and allow them to craft their jobs. Service managers should provide FSEs with social support and exercise empowering and supportive leadership to help them view STARA as a challenge rather than a threat.

Distinct from prior research on STARA awareness and employee outcomes, the study identified proactive service performance as a key outcome in the STARA context. By presenting self-efficacy and resilience as crucial personal resources that buffer FSEs from the deleterious impact of STARA awareness, the study provides practitioners with insights that can help FSEs maintain their job autonomy and proactive service performance in times of digitalization and automation.