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Social impact research remains in its infancy. The purpose of the paper is to build on Keeling and Marshall’s (2022) “Call for impact” paper and develop a comprehensive social impact pathway (SIP) framework. The aim is to encourage marketing researchers, non-profits and corporations to pursue impactful work that is valued, planned, monitored and evaluated.

The conceptual paper explores the complexities of estimating social impact drawing from a range of illustrative cases.

The paper identifies a lack of clarity in the understanding and application of impact and presents a pathway aimed at increasing focus on social impact across future work to deliver the net-positive changes that are needed to reverse biodiversity decline, climate change and social and health inequalities that continue to be persist and be experienced by so many planet wide.

This paper contributes a pathway forward to encourage and support increased utilisation of the framework in future marketing research.

Mapping and measuring SIPs are concerted efforts directing understanding towards identifying the activities that are contributing to the delivery of outputs that can achieve intended outcomes. The measurement of impact directs investment towards activities that ensure net-positive gains are achieved.

Ever growing social inequities, health disparities, loss of biodiversity and environmental degradation occur when practices are left unchecked. A focus on impact avoids greenwashing practices, ensuring that an understanding of what has changed because of the work is transparently reported.

This paper aims to encourage marketing researchers to engage in social change projects, rather than solely disseminating academic findings. Emphasising the importance of an outside-in approach, this paper highlights the necessity of showcasing accumulated outcomes to demonstrate impact.

This study investigates firms' innovation behaviour under environmental change. Therefore, it examines the effect of trade disputes on corporate technological innovation and how product market competition moderates this relationship.

This research tests the hypotheses using the fixed effects model based on panel data of publicly listed enterprises in China from 2007–2020.

The empirical results validate the positive association between trade disputes and corporate research and development (R&D) intensity as well as the U-shaped relationship between trade disputes and radical innovation. Additionally, the moderating effect of product market competition is verified: a concentrated market with less competition flattens the U-shaped curve of radical innovation induced by trade disputes; as the market becomes more concentrated and less competitive, the U-shaped relationship eventually turns into an inverted U.

First, this study contributes to the corporate innovation and trade dispute literature by expanding the environmental antecedents of technological innovation and the firm-level consequences of trade disputes. Second, this study enriches the theoretical framework of the environment–innovation link through an integrated perspective of contingency theory and dynamic capabilities view. Third, instead of the traditional linear mindset which had led to contradictory results, this study explores a curvilinear effect in the environment–innovation relationship.

The empirical studies of the options market efficiency have reported contradictory results, which sometimes confuse practitioners and academicians. The aim of this study was to clarify several aspects of options market efficiency by exploring the answers to two main questions: Under what conditions is the options market more efficient? Are the discrepancies in the estimated efficiency due to the reality of efficiency or mismeasurement?

Using a meta-analysis approach, 54 studies have been analyzed, which included 1,315 tests. The sum of the observations for all of the tests is 3.7 m observation sets. The effect size (type r) has been used to compare the different statistics in different studies. The cumulative effect size and its diversification have been calculated by the random effects model and Q statistic, respectively.

The most interesting finding of the study was that the options market, in all circumstances, is significantly inefficient. Another important finding was that the heterogeneity of options market efficiency is due to the complexity of pricing relations, test time, violation index and price type. To overcome this heterogeneity and accuracy, future studies should test the no-arbitrage options pricing relations at different times and by different price types, using complex and simple pricing relations and either mean violation or violation ratio efficiency measures.

Public disagreement about the options market efficiency in past studies means that this variable is heterogeneous in different conditions. As a significant contribution, this study develops the literature by proposing the causes of options market efficiency heterogeneity.

This research investigates Airbnb’s financial implications in emerging economies and their potential to influence stock market profitability.

Employing a multifaceted approach, the study combines parametric and nonparametric tests, robustness checks, and regression analysis to assess the impact of Airbnb’s announcements on emerging economy stock markets.

Airbnb’s announcements affect emerging economies' stock markets with a distinct pattern of cumulative abnormal returns (CAR): negative before the announcement and positive afterward. Informed investors strategically leverage this opportunity through short selling before the announcement and acquiring positions following it. Regression analysis validates these trends, revealing that stock index returns and inbound tourism affect CAR before announcements, while GDP growth influences CAR afterward. Announcements pertaining to emerging economies exert a more pronounced impact on stock indices compared to city-specific announcements, with COVID-19 period announcements demonstrating greater significance in abnormal returns than non-COVID-19 period announcements.

This study advances existing literature through a comprehensive range of statistical tests, differentiation between emerging countries and cities, introduction of five macroeconomic variables, and reliance on credible primary Airbnb data. It highlights the potential for investors to leverage Airbnb announcements in emerging markets for stock market profits, emphasizing the need for adaptive investment strategies considering broader macroeconomic factors.

This study considers a contracting problem between a fairness concerned entrepreneur (EN) and a fair-neutral venture capitalist (VC) to explore the effects of asymmetry, agency conflicts and fairness concerns.

The authors construct the model by assuming the EN's risk aversion degree is private information, which is more realistic but ignored in most studies. Under the principal–agent framework, the authors solve the VC's optimal contracting models by identifying the ranges of feasible solution, where the optimal solutions of these models are explicit and nicely reconcile the “private equity” puzzle. Moreover, validity of the optimal solutions is verified by numerical simulations.

In accordance with empirical evidence, information asymmetry lowers the optimal equity share that the VC provides to EN but raises EN's profit due to lower effort disutility and information rent. Moreover, the authors find that the fairness concerns is beneficial for the EN, where it not only increases the EN's optimal equity share, but also enhances the certainty equivalence of the EN's utility regarding its profit. Relative to the benchmark model where the EN's risk aversion degree is common knowledge, the EN's efforts recommended by the optimal contract is less sensitive to the EN's fairness concerns degree when the EN does not actually announce its risk aversion degree.

First, the authors incorporate asymmetry to study a two-period contracting problem and explore how it affects the equity shares allocated to the contractual parties. Second, the authors incorporate fairness concerns and analyze its effect regarding the decision-makings and profits.

Despite the government’s efforts to protect domestic industries from foreign competition through tariffs, the industrial sector’s contribution to GDP continued to decline in Nigeria. Based on the scenario, this study assessed the symmetric and asymmetric effects of tariffs on industrial performance in Nigeria for the period 1988–2021. Tariff was captured with a tariff rate applied to the weighted mean of all products, while industry value added as a percent of GDP was used as a proxy for industrial performance.

Linear and nonlinear ARDL techniques were used for the analysis.

The symmetric (linear ARDL) results revealed that tariffs have a significant positive effect on industrial performance in both the short and long term. The asymmetric (nonlinear ARDL) results showed that a long-term asymmetry exists between tariffs and industrial performance. It revealed positive effects on industrial performance for both positive and negative tariff changes, with the negative change having a greater impact.

Generally, the results showed that the use of tariffs to protect domestic industries in Nigeria promotes industrial performance. The implication is that the declining contribution of the industrial sector to GDP in Nigeria is not a result of the tariff policy. It shows that the government should look beyond tariff policy to enhance the industrial contribution to GDP.

Nigeria should exercise caution in using tariff policies to protect domestic industries to avoid retaliation from their trade partners that could reverse the positive impacts.

Understanding the factors that influence individuals’ adherence to social distancing is critical to effective policymaking in respiratory pandemics such as COVID-19. This study aims to explore the role of social factors in relation to social distancing measures.

Stratified convenience sampling was used in this survey research, involving 450 adults residing in both rural and urban areas of Aligodarz County, Lorestan, Iran.

The findings showed that approximately 14% of participants did not adhere to any of the assessed social distancing behaviors, while only around 30% adhered to all four assessed behaviors. On average, participants reported having 5.13 (SD = 3.60) close physical contact within the 24 h prior to completing the questionnaire. Bridging social capital and gender emerged as the most frequently observed predictors across the assessed social distancing measures. Additionally, age, employment status and residential setting were identified as influential factors for some of the evaluated measures.

This study contributes to the field by highlighting that the likelihood of non-adherence to social distancing measures tends to increase among male participants, those aged above 60, employed individuals, urban residents and those with a higher level of bridging social capital.

The Multi-Stakeholder Recommendation System learns consumer and producer preferences to make fair and balanced recommendations. Exclusive consumer-focused studies have improved the recommendation accuracy but lack in addressing producers' priorities for promoting their diverse items to target consumers, resulting in minimal utility gain for producers. These techniques also neglect latent and implicit stakeholders' preferences across item categories. Hence, this study proposes a personalized diversity-based optimized multi-stakeholder recommendation system by developing the deep learning-based diversity personalization model and establishing the trade-off relationship among stakeholders.

The proposed methodology develops the deep autoencoder-based diversity personalization model to investigate the producers' latent interest in diversity. Next, this work builds the personalized diversity-based objective function by evaluating the diversity distribution of producers' preferences in different item categories. Next, this work builds the multi-stakeholder, multi-objective evolutionary algorithm to establish the accuracy-diversity trade-off among stakeholders.

The experimental and evaluation results over the Movie Lens 100K and 1M datasets demonstrate that the proposed models achieve the minimum average improvement of 40.81 and 32.67% over producers' utility and maximum improvement of 7.74 and 9.75% over the consumers' utility and successfully deliver the trade-off recommendations.

The proposed algorithm for measuring and personalizing producers' diversity-based preferences improves producers' exposure and reach to various users. Additionally, the trade-off recommendation solution generated by the proposed model ensures a balanced enhancement in both consumer and producer utilities.

The present study examines the interplay between age, marital status, alpha female status and various adaptive performance dimensions among a cohort of 380 female professionals.

This study adopts a positivist approach to collect and analyse the data, utilizing appropriate statistical techniques to explore the relationships between the variables of interest.

The study elucidates the significant role of alpha female status in predicting adaptive performance. It finds that alpha females possess distinct competencies, particularly in learning and training, indicative of proactive behaviour and self-efficacy. While older participants tend to demonstrate higher performance levels, the study reveals no significant correlation between age and alpha female status, suggesting that leadership traits may develop independently of age. Furthermore, marital status exerts a modest influence on adaptive performance. The interplay of age and marital status significantly affects adaptive performance, potentially due to the Cumulative Advantage Paradigm, which is the accumulation of advantages or disadvantages throughout an individual's life course.

This study contributes to the existing literature by providing a nuanced understanding of how demographic factors converge to influence adaptive performance in professional settings. It highlights the importance of recognising and nurturing alpha females in organizations and considering the interactions between age and marital status when designing career development programmes and support systems.

Since smartphones became ubiquitous, online grocery and food purchases through take-away delivery platforms have steadily increased in China. Nevertheless, whether the development of take-away delivery can ameliorate urban–rural wage inequality still requires further analysis. The purpose of this paper is to clarify whether this positive effect exists.

This paper makes estimations based on city and individual levels combining the Chinese Household Income Project (CHIP) 2008, CHIP 2013, CHIP2018 survey data and the take-away delivery site data. At the city level, the Oaxaca-Blinder (O-B) decomposition method is employed to construct wage inequality index of urban and rural labors. At the individual level, this paper analyzes urban–rural wage differentials with high or low formal education level.

The rapid establishment of take-away delivery sites has resulted in an increase of 52.425 yuan on average in the annual wage of rural labors with low formal education level. When the cumulative number of sites increases by 1 unit, the annual wage inequality index decreases by 0.007 on average. Labors with the characteristics of rural household registration and low education can enjoy more dividends. Through inter-/within-industry decomposition, this paper elaborates formal education, age and cross-industry transfer as the main factors for the improvement of urban–rural wage inequality. Narrowing effect of wage differences between different groups in multiple sample slices also contributes to the mechanism analyses.

To the best of the author’s knowledge, this paper is the first to analyze the impact of take-away delivery development on the urban–rural wage inequality from the perspective of the establishment of take-away delivery sites. This empirical study will enrich the existing theoretical perspectives on urban–rural divide under the emergence of new forms of employment. The results indicate that new forms of employment represented by take-away delivery can not only promote economic growth, but also eliminate urban–rural inequality.