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The purpose of this study is to examine whether the institutional environment influences auditor reporting.

This study employs China's anti-corruption campaign as an exogenous shock to its institutional environment and compares auditors' issuance of modified audit opinions (MAOs) to small-profit clients before and during the campaign.

This study documents that small-profit clients were more likely to receive MAOs during the anti-corruption campaign period than before, indicating that auditors issued more conservative audit opinions to small-profit clients because of the anti-corruption campaign. Additionally, this study finds that increased auditor conservatism was more pronounced for auditors of large clients.

This study suggests that a weak institutional environment adversely affects auditor conservatism. This offers valuable insights for governments and regulators to improve the audit environment and for audit firms to enhance auditors' integrity and independence.

This study contributes to the research on institutional environments and auditing by observing a unique exogenous event.

The phenomenon of global brands taking a stance on crucial, yet polarizing, socio-political issues, namely global brand activism, is rising. However, how consumer views on this practice are shaped when global branding elements are factored in remains unclear. Drawing from the functional theory of attitude formation, this study investigates the relationships of consumer characteristics (political ideology, consumer ethnocentrism) and brand factors (global brand attitudes and perceived motivation of global brand activists) with attitudes toward global brand activists.

Using a survey of a UK nationally representative sample (n = 439), we test our hypothesized model via structural equation modeling and mediation analysis.

Our findings reveal direct and indirect effects of political ideology on attitudes toward global brand activists (AttGBACTIVs). While consumer ethnocentrism and global brand attitudes do not directly drive AttGBACTIVs, they do influence them indirectly. Perceived motivation of global brand activists emerges as a key mechanism activating these effects and affecting AttGBACTIVs.

First, this study constitutes a novel examination of consumer views of brand activism through a global branding lens. Second, our investigation uniquely combines important determinants of brand activism outcomes with key international marketing factors (namely consumer ethnocentrism and global brand attitudes). Third, the concurrent exploration of individual and brand factors in our mediated model reveals the complex mechanisms through which attitudes toward global brand activists are formed.

Despite the important role that suppliers have in enhancing the environmental performance of a buyer firm, previous research has not investigated the individual-level motivations of supplier employees (representatives) in supplier-to-supplier environmental knowledge sharing. Thus, we use insights from the coopetition literature to examine how buyer firms can encourage supplier-to-supplier environmental knowledge sharing with the aim of improving the buyer’s environmental performance.

We empirically test our model using an online vignette-based experiment administered to supply chain managers. We contextualized our results using insights from interviews with senior managers representing firms operating in a broad array of industries.

We find that a supplier representative’s personal environmental values influence their commitment to an environmental consortium with a rival firm, and they are subsequently willing to share proprietary environmental knowledge. In turn, these relationships are moderated by situational factors including competitive intensity and buyer power.

The study of coopetition is an emerging stream of research in operations management. Our findings improve the understanding on how a focal actor within a buyer–supplier coopetitive network can promote environmental knowledge sharing behavior.

This study aims to investigate the intricate relationships between a community energy system, water resources and biodiversity conservation, with a specific focus on augmenting community energy resilience in Bondo. The primary objective is to gain an in-depth understanding of how community members perceive and experience the challenges related to balancing the often-conflicting demands of energy, water and biodiversity conservation within this context.

The research uses a qualitative approach to unravel the multifaceted dynamics of community energy systems, water resources and biodiversity conservation in Bondo. Data were collected through focus groups and direct observations, enabling a nuanced exploration of community perspectives and lived experiences. The subsequent analysis of this qualitative data follows established thematic analysis procedures.

The study's findings shed light on the formidable barriers that impede rural communities in Malawi from accessing electricity effectively. Even in communities fortunate enough to have electricity connections, the lack of knowledge regarding productive electricity use results in community energy systems operating at significantly reduced load factors. Furthermore, the intricate challenge of managing a biodiversity hotspot persists, exacerbated by the densely populated peripheral communities' continued reliance on forest, land and water resources. These activities, in turn, contribute to ecosystem degradation.

In a context where government-led management of forest reserves and game reserves has not yielded the expected results due to a multitude of factors, there arises a compelling need for innovative approaches. One such innovation involves fostering partnerships between the government and experienced trusts as lead organisations, providing a fresh perspective on addressing the complex interplay between community energy systems, water resources and biodiversity conservation. This novel approach opens doors to explore alternative pathways for achieving the delicate balance between human energy needs and the preservation of vital ecosystems.

This study uses social exchange theory to describe, explain and propose the influence of dyad partners' leadership position structure, which includes the roles they play and their existing and prospective common experience, on their commitment to their dyad and their cooperation.

The study uses the case of equally empowered co-CEOs in a family business, who play the roles of family member, owner and executive; co-CEOs in a startup firm, who play the roles of owner and executive; and co-CEOs in a merger and acquisition (M&A), who play the role of executive. Co-CEOs in family businesses benefit from longer existing and longer prospective dyad longevity than co-CEOs in startups, who, in turn, benefit from longer existing and longer prospective dyad longevity than co-CEOs in M&As.

The study proposes that the roles the partners play in the dyads, and the existing and prospective longevity of their relationship, positively influence the partners' commitment to the dyad and their level of cooperation.

The study offers a model that has the potential to direct scholars at the formulation of the theory of top management symmetric formal power dyads dynamics and assist family business owners, startup partners, board of directors and co-CEOs in formulating and implementing upper echelons leadership plans to enhance cooperation and coordination between equal partners.

Because the dynamic characteristics of the stock market are nonlinear, it is unclear whether stock prices can be predicted. This paper aims to explore the predictability of the stock price index from a long-memory perspective. The authors propose hybrid models to predict the next-day closing price index and explore the policy effects behind stock prices. The paper aims to discuss the aforementioned ideas.

The authors found a long memory in the stock price index series using modified R/S and GPH tests, and propose an improved bi-directional gated recurrent units (BiGRU) hybrid network framework to predict the next-day stock price index. The proposed framework integrates (1) A de-noising module—Singular Spectrum Analysis (SSA) algorithm, (2) a predictive module—BiGRU model, and (3) an optimization module—Grid Search Cross-validation (GSCV) algorithm.

Three critical findings are long memory, fit effectiveness and model optimization. There is long memory (predictability) in the stock price index series. The proposed framework yields predictions of optimum fit. Data de-noising and parameter optimization can improve the model fit.

The empirical data are obtained from the financial data of listed companies in the Wind Financial Terminal. The model can accurately predict stock price index series, guide investors to make reasonable investment decisions, and provide a basis for establishing individual industry stock investment strategies.

If the index series in the stock market exhibits long-memory characteristics, the policy implication is that fractal markets, even in the nonlinear case, allow for a corresponding distribution pattern in the value of portfolio assets. The risk of stock price volatility in various sectors has expanded due to the effects of the COVID-19 pandemic and the R-U conflict on the stock market. Predicting future trends by forecasting stock prices is critical for minimizing financial risk. The ability to mitigate the epidemic’s impact and stop losses promptly is relevant to market regulators, companies and other relevant stakeholders.

Although long memory exists, the stock price index series can be predicted. However, price fluctuations are unstable and chaotic, and traditional mathematical and statistical methods cannot provide precise predictions. The network framework proposed in this paper has robust horizontal connections between units, strong memory capability and stronger generalization ability than traditional network structures. The authors demonstrate significant performance improvements of SSA-BiGRU-GSCV over comparison models on Chinese stocks.