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How does context shape the way in which corporations contribute to or impede progress toward sustainable development goals (SDGs)? In this chapter, the author studies how the state as corporate owner and in its broader function in the institutional environment affects companies’ involvement in misbehaving practices related to human rights issues, with a focus on the banking industry. Based on a longitudinal analysis of 178 banks over the cohort 1996–2018, the results show that state-owned banks, as well as those from institutionally weak environments, are more involved in business-related misbehaving practices. Moreover, in a strong institutional environment, state-owned banks are more involved in corporate misbehavior than non-state-owned banks. These results contribute to the literature on corporate misbehavior, focusing on the state’s role in preventing or facilitating banks’ involvement in misbehaving practices. The author concludes by discussing the findings’ implications and providing suggestions for future research.

An emerging application of Big Data is the addition of sensors and other micro‐electronic devices to engineer‐to‐order (ETO) goods such as one‐of‐a‐kind buildings and ships. The addition of micro‐electronic devices can enable the setting up and operation of smart buildings and smart ships. The purpose of this paper is to provide a critical realist analysis of Big Data hype. This is necessary to determine what challenges will need to be met before project businesses can achieve informational effects and transformational effects from Big Data technologies.

A critical realist study informed by reference to predictive theory and findings from action research. The predictive theory is concerned with the three different types of business effects that can come from information and communication technologies (ICTs): automational, informational, and transformational.

Critical realist analysis reveals that hype about Big Data underplays many challenges in achieving informational and transformational effects.

Many inter‐related non‐trivial factors need to be taken into account when considering investing in Big Data initiatives. These factors range from the planning of data sampling rates, through the robust fixing of sensors, to the implementation of data mining algorithms and signal models.

The originality of this paper is that critical realism is used in analysis of Big Data hype. The value of this paper is that it reveals a causal mechanism and causal context for project business Big Data application. This type of critical realist analysis can be applied to enable better understanding of necessary causal mechanisms and causal contexts for other ICT innovations.

This study aims to take a whole-of-chain perspective to explore how entrepreneurial orientation (EO) influences collaborative performance in agri-food value-chains through enhancing the acquisition of knowledge.

Data were collected through a survey of 233 actors, including farmers, intermediaries and retailers in one beef cattle value-chain in the Central Highlands, Vietnam. Structural equation modeling was used to test hypotheses.

The actors’ level of EO within a value-chain is positively associated with collaborative performance within the beef value-chain. Additionally, knowledge acquisition partially mediates the relationship between EO and collaborative performance.

Generalizability is limited because of sampling constraints.

To the best of the authors’ knowledge, this is the first study of EO from a whole-of-chain perspective in agri-food value-chains in an emerging economy and has implications for policymakers and agri-food marketers.

The study aims to determine whether a relationship exists between the potential significance of corporate controversies for stakeholders and how organisations respond to them in their annual and sustainability reports.

This paper employs content analysis on annual and sustainability reports of 48 listed companies from the Refinitiv database. The logit regression was used to estimate the model.

The study revealed that the main factors increasing the probability of a controversial issue being addressed in a corporate report are the controversy’s potential significance, companies’ financial performance and lawsuits.

Our study has three major limitations. These are a relatively small sample of companies and reports, focusing on disclosures made in corporate reports and omitting other channels of communication, for example, social media, and a certain amount of subjectivity in the process of coding information.

Former studies show that corporations face a serious risk of their hypocritical strategies becoming too evident for stakeholder groups. Our findings suggest that the risk is already materialising and may undermine the idea of CSR and sustainability reporting.

Our research focuses on high-profile adverse incidents widely reported in the media, the omission of which from corporate reports seems to constitute a particular case of organised hypocrite. It also demonstrates that companies use an impression management strategy to defuse adverse publicity and that major controversies cause minor ones to be omitted from their reports.

Direction-of-arrival (DOA) estimation for wideband sources has attracted a growing interest in the recent decade because wideband sources are incorporated in many real-world applications such as communication systems, radar, sonar and acoustics. One way to estimate the DOAs of wideband signals is to decompose it into narrowband signals using discrete Fourier transform (DFT) and then apply well-established narrowband algorithms to each signal. Afterwards, results are averaged to yield the final DOAs. These techniques require scanning the full band of wideband sources, ultimately degrading the resolution and increasing complexity. This paper aims to propose a new DOA estimation methodology to solve these problems.

The new DOA estimation methodology is based on incoherent signal subspace method (ISSM). The proposed approach presents a criterion to select a single sub-band of the selected narrowband signals instead of scanning the whole signal spectrum. Then, the DOAs of wideband signals are estimated using the selected sub-band. Therefore, it is named as single sub-band (SSB)-ISSM.

The computational complexity of the proposed method is much lower than that of traditional DFT-based methods. The effectiveness and advantages of the proposed methodology are theoretically investigated, and computational complexity is also addressed.

To verify the theoretical analysis, computer simulations are implemented, and comparisons with other algorithms are made. The simulation results show that the proposed method achieves better performance and accurately estimates the DOAs of wideband sources.

This study aims to crystallize the research landscape of corporate social responsibility (CSR) authenticity by systematically analyzing CSR scholarships published in peer-reviewed journals from 2007 to 2021.

Quantitative content analysis was used to systematically analyze 52 peer-reviewed articles on CSR authenticity. In particular, this study coded the conceptualizations and operationalizations of CSR authenticity, research contexts, applied theoretical frameworks and constructs associated with authenticity in the CSR scholarships.

This study’s analysis revealed that CSR authenticity is a multifaceted and multidimensional concept researched in various contexts. Yet, it still lacks clear and consistent conceptualization and theorization. Methodologically, qualitative and quantitative methods have equally contributed to the investigation of CSR authenticity. However, scale development and validation still need to improve.

The sample of this research is limited by the searching method and language restriction. This research contributes to CSR scholarships by describing the growing landscape of CSR authenticity research, identifying key research gaps and offering suggestions for future research.

Practitioners can use the findings as references to develop more authentic CSR activities.

This study is an early attempt to examine the research on CSR authenticity, which has been inconclusive and disorganized, despite the rapid growth of publications in recent years.

This study aims to focus on automated text analyses (ATAs) of sustainability and integrated reporting as a recent approach in empirical–quantitative research.

Based on legitimacy theory, the author conducts a structured literature review and includes 38 quantitative peer-reviewed empirical (archival) studies on specific determinants and consequences of sustainability and integrated reporting. The paper makes a clear distinction between analyses of reports due to readability, tone, similarity and specific topics. In line with prior studies, it is assumed that more readable reports with less tone and similarity relate to increased reporting quality.

In line with legitimacy theory, there are empirical indications that specific corporate governance variables, other firm characteristics and regulatory issues have a main impact on the quality of sustainability and integrated reporting. Furthermore, increased reporting quality leads to positive market reactions in line with the business case argument.

The author deduces useful recommendations for future research to motivate researchers to include ATA of sustainability and integrated reports. Among others, future research should recognize sustainable and behavioral corporate governance determinants and analyze other stakeholders’ reactions.

As both stakeholders’ demands on sustainability and integrated reporting have increased since the financial crisis of 2008–2009, firms should increase the quality of reporting processes.

This analysis makes major contributions to prior research by including both sustainability and integrated reporting, based on ATA. ATAs play a prominent role in recent empirical research to evaluate possible drivers and consequences of sustainability and integrated reports. ATA may contribute to increased validity of empirical–quantitative research in comparison to classical manual content analyses, especially due to future CSR washing analyses.