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The paper aims to reveal the impact of relationship marketing (RM) practices adopted by companies in emerging markets on their market and financial performance (FP) over a long-term, 13-year perspective.

The research design combines primary empirical data from 229 Russian companies, based on the Contemporary Marketing Practices (CMP) survey, and objective FP data from official statistical databases for 2008–2020 to verify the impact of RM practices on market and FP in the long term.

The research underlines the significant impact of RM practices. It is important to notice that the effect of product development (PD) on marketing performance is mediated by competitor orientation. PD affects market and FP, whose roles vary with the return on assets (ROA).

Research design supplements the subjective survey data with the objective FP data on the ROA to avoid common method bias.

Implementation of RM practices by Russian companies can increase their effectiveness of performance in the long term.

This research shows the positive impact of RM practices on the FP of Russian firms over the past 13 years.

In the extant literature, the concepts of charity and philanthropy have been differentiated based on the belief that charity stems from religious motivations and philanthropy is often secular in origin. Accordingly, this paper aims to investigate whether there is a distinction between managerial practices regarding the given concepts as emphasized in the conceptual discussions.

To see the managerial practices, the authors determined bazaars, community fundraising events organized by nonprofit organizations (NPOs), as the research field. Then, this study followed the general systematic of qualitative research. Accordingly, the authors conducted 44 interviews with experienced bazaar organizers from 10 NPOs in total. Furthermore, four days of participant observation with field notes were made in each bazaar, which lasted from 7 to 10 days. This study also used archival data as a secondary data source and then analyzed all data with a content analysis technique.

This study found that the field practices mainly do not support the distinction drawn over the conceptual discussions. Both concepts are nouns describing the act of giving and helping the needy. They are actively performed based on different motives (religion-based and secular).

The relevant distinction is limited to the conceptual discussions and has not been supported by the findings obtained from the field. Also, most of the studies on helping were carried out in the Western context. Studies conducted outside these cultures are quite limited. The value of the current study lies in the fact that it was conducted in a cultural context different from the Western cultures and paves the pathway for future research.

The purpose of this study is to comprehend how AI aids marketers in engaging customers and generating value for the company by way of customer engagement (CE). CE is a popular area of research for scholars and practitioners. One area of research that could have far-reaching ramifications with regard to strengthening CE is artificial intelligence (AI). Consequently, it becomes extremely important to understand how AI is helping the marketer reach customers and create value for the firm via CE.

A detailed approach using both systematic review and bibliometric analysis was used. It involved identifying key research areas, the most influential authors, studies, journals, countries and organisations. Then, a comprehensive analysis of 50 papers was carried out in the four identified clusters through co-citation analysis. Furthermore, a content analysis of 42 articles for the past six years was also conducted.

Emerging themes explored through cluster analysis are CE concepts and value creation, social media strategies, big data innovation and significance of AI in tertiary industry. Identified themes for content analysis are CE conceptualisation, CE behaviour in social media, CE role in value co-creation and CE via AI.

CE has emerged as a topic of great interest for marketers in recent years. With the rapid growth of digital media and the spread of social media, firms are now embarking on new online strategies to promote CE (Javornik and Mandelli, 2012). In this review, the authors have thoroughly assessed multiple facets of prior research papers focused on the utilisation of AI in the context of CE. The existing research papers highlighted that AI-powered chatbots and virtual assistants offer real-time interaction capabilities, swiftly addressing inquiries, delivering assistance and navigating customers through their experiences (Cheng and Jiang, 2022; Naqvi et al., 2023). This rapid and responsive engagement serves to enrich the customer’s overall interaction with the business. Consequently, this research can contribute to a comprehensive knowledge of how AI is assisting marketers to reach customers and create value for the firm via CE. This study also sheds light on both the attitudinal and behavioural aspects of CE on social media. While existing CE literature highlights the motivating factors driving engagement, the study underscores the significance of behavioural engagement in enhancing firm performance. It emphasises the need for researchers to understand the intricate dynamics of engagement in the context of hedonic products compared to utilitarian ones (Wongkitrungrueng and Assarut, 2020). CEs on social media assist firms in using their customers as advocates and value co-creators (Prahalad and Ramaswamy, 2004; Sawhney et al., 2005). A few of the CE themes are conceptual in nature; hence, there is an opportunity for scholarly research in CE to examine the ways in which AI-driven platforms can effectively gather customer insights. As per the prior relationship marketing studies, it is evident that building relationships reduces customer uncertainty (Barari et al., 2020). Therefore, by using data analysis, businesses can extract valuable insights into customer preferences and behaviour, equipping them to engage with customers more effectively.

The rapid growth of social media has enabled individuals to articulate their thoughts, opinions and emotions related to a brand, which creates a large amount of data for VCC. Meanwhile, AI has emerged as a radical way of providing value content to users. It expands on a broader concept of how software and algorithms work like human beings. Data collected from customer interactions are a major prerequisite for efficiently using AI for enhancing CE. AI not only reduces error rates but, at the same time, helps human beings in decision-making during complex situations. Owing to built-in algorithms that analyse large amounts of data, companies can inspect areas that require improvement in real time. Time and resources can also be saved by automating tasks contingent on customer responses and insights. AI enables the analysis of customer data to create highly personalised experiences. It can also forecast customer behaviour and trends, helping businesses anticipate needs and preferences. This enables proactive CE strategies, such as targeted offers or timely outreach. Furthermore, AI tools can analyse customer feedback and sentiment across various channels. This feedback can be used to make necessary improvements and address concerns promptly, ultimately fostering stronger customer relationships. AI can facilitate seamless engagement across multiple digital channels, ensuring that customers can interact with a brand through their preferred means, be it social media, email, or chat. Consequently, this research proposes that practitioners and companies can use analysis performed by AI-enabled systems on CEB, which can assist companies in exploring the extent to which each product influences CE. Understanding the importance of these attributes would assist companies in developing more memorable CE features.

This study examines how prominent CE and AI are in academic research on social media by identifying research gaps and future developments. This research provides an overview of CE research and will assist academicians, regulators and policymakers in identifying the important topics that require investigation.

Allocation of the marketing budget has become increasingly challenging due to the diverse channel exposure to customers. This study aims to enhance global marketing knowledge by introducing an ensemble attribution model to optimize marketing budget allocation for online marketing channels. As empirical research, this study demonstrates the supremacy of the ensemble model over standalone models.

The transactional data set for car insurance from an Indian insurance aggregator is used in this empirical study. The data set contains information from more than three million platform visitors. A robust ensemble model is created by combining results from two probabilistic models, namely, the Markov chain model and the Shapley value. These results are compared and validated with heuristic models. Also, the performances of online marketing channels and attribution models are evaluated based on the devices used (i.e. desktop vs mobile).

Channel importance charts for desktop and mobile devices are analyzed to understand the top contributing online marketing channels. Customer relationship management-emailers and Google cost per click a paid advertising is identified as the top two marketing channels for desktop and mobile channels. The research reveals that ensemble model accuracy is better than the standalone model, that is, the Markov chain model and the Shapley value.

To the best of the authors’ knowledge, the current research is the first of its kind to introduce ensemble modeling for solving attribution problems in online marketing. A comparison with heuristic models using different devices (desktop and mobile) offers insights into the results with heuristic models.

The purpose of this study was to analyze the effects of social media analytics on firm performance using a sample of small and medium enterprises (SMEs) in Thailand. This study also investigated whether entrepreneurial orientation (EO) moderated the effects of social media analytics on firm performance.

This study used SMEs listed in the Department of Business Development of Thailand as the sampling frame. Probability sampling was used to draw the sample. A questionnaire survey was used to collect data from 334 firms. The data were analyzed using partial least squares structural equation modeling.

The results supported the positive association between social media analytics practices on firm performance. Moreover, this study found that EO moderated this association significantly. In particular, the positive association between social media analytics practices on firm performance was higher for firms that exhibit a high EO than those that exhibit a low EO. This result indicated that firms that implement social media analytics practices achieved higher performance when they exhibited a high EO.

Social media data analytics should be implemented to strengthen the technological competence of firms. Moreover, firms should integrate EO practices into their implementation of social media analytics to increase their ability to generate substantial improvements in their strategic implementation, thereby enabling them to gain sustainable competitiveness in their market.

Because SMEs are the driving force for economic growth and development in Thailand, their ability to achieve higher performance when they effectively integrate EO practices into their implementation of social media data analytics could be beneficial for the sustainable development of Thailand, especially in the current data-driven era.

The result that EO moderates the effect in enhancing social media analytics practices’ influence on firm performance provides new knowledge that extends the boundary of research on this topic. The authors provided a theoretical explanation to clarify the way the implementation of social media analytics practices should be integrated with EO to increase the level of performance that firms achieve from such practices.

Within the current institutional landscape, characterized by increased societal and governmental emphasis on environmental preservation, there is growing interest in the potential of digital transformation (DT) to advance the circular economy (CE). Nonetheless, the empirical substantiation of the connection between DT and CE remains limited. This study seeks to investigate the impact of DT on CE at the organizational level and examine how various institutional factors may shape this relationship within the Chinese context.

To scrutinize this association, we construct a research framework and formulate hypotheses drawing on institutional theory, obtaining panel data from 238 Chinese-listed high-tech manufacturing firms from 2006 to 2019. A regression analysis approach is adopted for the sample data.

Our regression analysis reveals a positive influence of DT on CE performance at the organizational level. Furthermore, our findings suggest that the strength of this relationship is bolstered in the presence of heightened regional institutional development and industry competition. Notably, we find no discernible effect of a firm’s political connections on the DT–CE performance nexus.

This study furnishes empirical evidence on the relationship between DT and CE performance. By elucidating the determinants of this relationship within the distinct context of Chinese institutions, our research offers theoretical and practical insights, thus laying the groundwork for subsequent investigations into this burgeoning area of inquiry.

The discussion on international migration has become a significant part of globalization and a topical issue in international relations, especially in developing economies which mostly relies on migrant remittances. The purpose of the study is to examine whether financial market development (equity market development and banking sector development) really drives migrant remittance flow in Sub-Saharan Africa (SSA).

The study employs the dynamic heterogeneous panel data approach-the pool mean group (PMG) and the mean group (MG) techniques in analyzing the model based on data obtained from 27 SSA countries covering the period 2000–2020.

The findings of the study revealed that financial market development (equity market development and banking sector development) is a key driver of migrant remittances flows in the SSA region. In addition, the study revealed that the following macroeconomic variables such as real interest rate, unemployment rate, global growth, emigration, and economic growth are also determinants of migrant remittances flows in the SSA region.

The reviewed empirical literature revealed that several studies documents that the macroeconomic determinants of migrant remittances include inflation, GDP, interest rate, exchange rate, population growth, financial sector development and unemployment rate. Most of these studies fail to capture both equity market development and robust banking sector development (financial market development) as critical drivers of migrant remittances flow in SSA. Also, this study uses a robust measure of equity market development and banking sector development, unlike previous studies.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0361

This study empirically investigates the relationship between goodwill assets and capital structure (i.e. debt ratio) of firms and the moderating effect of financial market development on the relationship between goodwill assets and capital structure.

This research applied a quantitative method. The article collects large samples of listed firms from 23 developing and nine developed countries and applied the panel data techniques. This research used firm-level data from the DataStream database for both developed and developing countries. The study uses 4,912 firm-level data from 23 developing countries and 4,303 firm-level data from nine developed countries.

The findings reveal a significant positive relationship between goodwill assets and capital structure in developing countries, but goodwill assets have a significant negative relationship with capital structure in developed countries. Moreover, financial market development positively moderates the relationship between goodwill assets and the capital structure of firms in developing countries. The results inform firm managers that goodwill assets serve as additional collateral to secure debt financing. Moreover, policymakers should formulate a debt market policy that recognizes goodwill assets as additional collateral for the purpose of obtaining debt capital.

The study has several implications. First, goodwill assets are identified as a factor of capital structure in this study. Fixed assets have been identified as one of the drivers of capital structure in previous research, although goodwill assets are seldom included. Second, this article shows that along with demand-side determinants, supply-side determinants also play an important role in terms of the firms' choice about the capital structure. Therefore, firms should take both the demand-side and supply-side factors into consideration when sourcing for external financing (i.e. debt capital).

The study considered goodwill as a component of capital structure. The study analysis includes a large sample of enterprises, including 4,912 big firms from 23 developing countries and 4,303 large firms from nine industrialized or developed countries, which adds to the current capital structure information. Furthermore, a large sample size increases the results' robustness and generalizability.

The rising concern for the accuracy of residential valuations in Nigeria has created the need for key stakeholders in the residential property markets in the study areas to know the level of accuracy of valuations in order to make rational residential property transactions, amongst other purposes.

A blend of descriptive and causal designs was adopted for the study. Data were collected via structured questionnaire administered to 179 estate surveying and valuation (ESV) firms in the study areas using census sampling technique. Analytical techniques such as median percentage error (PE), mean and relative importance index (RII) analysis were employed in the analysis of data collected for the study.

The study found that valuation accuracy is greater in the residential property market in Abuja than in Minna, with inappropriate valuation methodology as the most significant cause of valuation inaccuracy.

The practical implication of this study is that a reliable databank should be established for the property market to provide credible transaction data for valuers to conduct accurate valuations in these cities. Strict enforcement of national and international valuation standards by the regulatory authorities as well as retraining of valuers on appropriate application of valuation approaches and methods are the recommended corrective measures.

No study has comparatively examined the accuracy of valuations in two extremely different residential property markets in the country using actual valuation and transaction prices.

This research aims to examine the effects of corporate digital transformation on firm value, with a particular focus on the mediating roles played by cost leadership and differentiation strategies.

This study employs word frequency analysis to create corporate digital transformation indicators and determine how corporate digital transformation impacts firm value. The data used in the analysis comes from 2,056 listed manufacturing enterprises in China between 2010 and 2019.

This study demonstrates that digital transformation has a favorable impact on firm value, and that cost leadership strategy and differentiation strategy significantly mediate the relationship between both of them.

This study utilized word frequency analysis to assess the state of corporate digital transformation. It lacked a more thorough description of internal production processes, operational efficiency, and the pace of digital transformation.

The results of this study can not only promote the digital transformation and firm value, but also provide a theoretical basis for enterprises to choose a reasonable competitive strategy in the digital transformation.

This study contributes significantly to the field of firm value research by including digital transformation as a fundamental component. Furthermore, it investigates how cost leadership strategy and differentiation strategy play mediating roles, providing a new perspective and explanatory mechanism for understanding the influence of digital transformation on firm value.