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The purpose of this study is to evaluate the linkage between stock markets in Middle Eastern countries before and during the COVID-19 pandemic by using daily and monthly data sets for the period from 2011 to 2021.

The multivariate BEKK-GARCH model was computed to evaluate the existence of non-linear linkage among Middle Eastern stock markets. A correlation approach was used in this study to determine the type of linear connectivity between Middle Eastern stock markets. The study used monthly and daily data sets covering the years 2011 to 2021 to investigate the linkage between stock returns and the volatility spillover between the stock markets in Palestine, Jordan, Syria and Lebanon, both before and during COVID-19. To understand the types of relationships between markets before and during COVID-19, the daily data set was split into two periods.

Results from the pre-COVID-19 suggest that the Syria stock market is not related to any stock market in the Middle East markets; the Palestine and Lebanon stock markets exhibit a weak relationship, but Jordan and Palestine stock markets are strongly linked. Conversely, results from COVID-19 evince a very strong bidirectional volatility spillover between Middle East stock markets. Overall, the results indicate the existence of increased linkage during the COVID-19.

The data collection on a daily and monthly basis, both before and during COVID-19, presents certain limitations for the paper. Another limitation is that the data cannot be generalized to all other Middle Eastern countries; rather, the conclusions drawn can only be applied to these four countries. This is especially true if the scholars collected most of the necessary data but were unable to obtain certain data for various reasons.

These findings have implications for risk management, market regulation and the growth of local stock markets. Facilitating the growth of smaller, more specialized markets to improve integration with other Middle Eastern markets is one of the goals of the domestic stock market development policy. To ensure financial stability, Middle Eastern stock market linking policies should consider spillover risk and take steps to minimize it. Enhancing the range of investment opportunities accessible to shareholders and functioning as confidential risk-sharing mechanisms to facilitate improved risk management in Middle Eastern stock markets will not only significantly influence the mobilization of private capital to promote investment and local economic growth but also lay groundwork for integrated market platforms.

This paper adds to the body of literature by demonstrating the nature of the connections between these small markets and the larger markets in the Middle East region. Information from the smaller markets provides institutional insights that enhance the body of existing research, guide the formulation of evidence-based policies and advance financial literacy in these markets. This study contributes by comparing data from different stock markets to better understand the type and strength of the link and relationship between Middle Eastern stock markets, as well as any underlying or reinforcing factors that might have contributed to the relationship and the specific types of links that these markets shared prior and during COVID-19.

Drawing on the resource-based view, this study examines the effect of distribution adaptation on export performance. The study also examines the moderating role of responsiveness and commitment. Two distinct factors for commitment (i.e. managerial export commitment and financial export commitment) and two distinct factors for responsiveness (i.e. export customer responsiveness and export competitor responsiveness) are considered as moderators in the relationship between distribution adaptation and export performance.

Using a Spanish governmental database of exporting firms, this study collected data from 208 firms to run the analysis.

The results indicate that distribution adaptation has a positive impact on export performance. Findings also support the moderating roles of the two types of commitment and the two types of responsiveness. Managerial export commitment positively moderates the relationship, whereas financial export commitment plays a negative moderating role. Both export customer responsiveness and export competitor responsiveness have a positive moderating impact.

To consider distribution adaptation as a distinct variable rather than mixing it with other elements of the marketing mix. This distinction facilitates a clearer comprehension of its unique contribution to export performance. Two distinct factors for commitment and two distinct factors for responsiveness are considered. This approach offers a more detailed analysis of how the different aspects of commitment and responsiveness moderate this relationship.

Marketing professionals are under pressure to implement methods and metrics that demonstrate the value of the function. This paper aims to propose a model to measure marketing performance, focusing on four categories of metrics and two types of factors that influence the effectiveness of the assessment process.

The paper is organized in three parts. The first part includes a synthesis of the theoretical background on the subject. Next, the rationale and architecture of the model are presented, together with an explanation of the elements that compose it. A reflection on the work developed is presented in the last section.

Benefits regarding how to best assess marketing practice are considerable, as organizations with effective performance measurement systems tend to show better results than others. In this context, the choice of metrics is important, but it is also necessary to understand the mechanisms through which the effectiveness of the measurement process can be improved.

Literature has mainly focused attention on the effect of individual programs on specific measures or on conceptual models that do not sufficiently address all major elements in the marketing assessment process. This work extends previous contributions on the subject, presenting a model that combines metrics with factors underlying the measurement process.

As specific objectives, we intend to: (1) measure the connectivity between the spillovers of returns from the financial and nonfinancial sectors of the Brazilian stock market; (2) estimate the spillovers of individual returns for each sector to identify periods of higher and lower profits over a period of around eight years; (3) investigate the existence of relationships between these repercussions between pairs of sectoral indices, evaluating how much each specific sector transfers to each other and the market as a whole and (4) examine whether the connectivity of the Brazilian stock market itself and future interest rates in the USA and Brazil as well as the risk of the Brazilian economy, were explanatory variables of the dynamics of interdependence in the returns of these indices.

With a daily series of closing prices of sectoral indices from March 3, 2015, until June 21, 2023, we researched eight of the most relevant sectoral indices on the São Paulo Stock Exchange (B3). With this data, we estimate the Diebold–Yilmaz spillover index and frequency decompositions of Barunik–Krehlik.

The conclusions indicate that there is an overall connection of 66% in the financial and nonfinancial sectoral indices, with a peak of 83%. The consumer, energy and public services sectors stand out as significant sources of primary spillovers. When we classified secondary effects into periods, we saw that the shocks dissipated as time passed and the returns of the commodity index remained resilient across all periods.

Our conclusions highlight the influence of three main factors in sectors with a high degree of connectivity: periods of increased uncertainty; negative externalities in post-crisis periods and the impact of financial news on market sentiment. We think this study provides information that can be useful for policymakers, investors, investment portfolio managers, economists (financial, monetary and industrial), investment consultants and researchers who are interested in the complex interconnection among emerging market stock indices.

Objectively evaluating the fairness of the algorithm, exploring in specific scenarios combined with scenario characteristics and constructing the algorithm fairness evaluation index system in specific scenarios.

This paper selects marketing scenarios, and in accordance with the idea of “theory construction-scene feature extraction-enterprise practice,” summarizes the definition and standard of fairness, combs the application link process of marketing algorithms and establishes the fairness evaluation index system of marketing equity allocation algorithms. Taking simulated marketing data as an example, the fairness performance of marketing algorithms in some feature areas is measured, and the effectiveness of the evaluation system proposed in this paper is verified.

The study reached the following conclusions: (1) Different fairness evaluation criteria have different emphases, and may produce different results. Therefore, different fairness definitions and standards should be selected in different fields according to the characteristics of the scene. (2) The fairness of the marketing equity distribution algorithm can be measured from three aspects: marketing coverage, marketing intensity and marketing frequency. Specifically, for the fairness of coverage, two standards of equal opportunity and different misjudgment rates are selected, and the standard of group fairness is selected for intensity and frequency. (3) For different characteristic fields, different degrees of fairness restrictions should be imposed, and the interpretation of their calculation results and the means of subsequent intervention should also be different according to the marketing objectives and industry characteristics.

First of all, the fairness sensitivity of different feature fields is different, but this paper does not classify the importance of feature fields. In the future, we can build a classification table of sensitive attributes according to the importance of sensitive attributes to give different evaluation and protection priorities. Second, in this paper, only one set of marketing data simulation data is selected to measure the overall algorithm fairness, after which multiple sets of marketing campaigns can be measured and compared to reflect the long-term performance of marketing algorithm fairness. Third, this paper does not continue to explore interventions and measures to improve algorithmic fairness. Different feature fields should be subject to different degrees of fairness constraints, and therefore their subsequent interventions should be different, which needs to be continued to be explored in future research.

This paper combines the specific features of marketing scenarios and selects appropriate fairness evaluation criteria to build an index system for fairness evaluation of marketing algorithms, which provides a reference for assessing and managing the fairness of marketing algorithms.

Algorithm governance and algorithmic fairness are very important issues in the era of artificial intelligence, and the construction of the algorithmic fairness evaluation index system in marketing scenarios in this paper lays a safe foundation for the application of AI algorithms and technologies in marketing scenarios, provides tools and means of algorithm governance and empowers the promotion of safe, efficient and orderly development of algorithms.

In this paper, firstly, the standards of fairness are comprehensively sorted out, and the difference between different standards and evaluation focuses is clarified, and secondly, focusing on the marketing scenario, combined with its characteristics, key fairness evaluation links are put forward, and different standards are innovatively selected to evaluate the fairness in the process of applying marketing algorithms and to build the corresponding index system, which forms the systematic fairness evaluation tool of marketing algorithms.

This paper investigates share price clustering and its determinants across Nasdaq Stockholm, Copenhagen, Helsinki, and Iceland.

This paper investigates share price clustering and its determinants across Nasdaq Stockholm, Copenhagen, Helsinki, and Iceland. Univariate analysis confirms widespread clustering, notably favouring closing prices ending in zero. Multivariate analysis explores the impact of firm size, price level, volatility, and turnover on clustering.

Univariate analysis confirms widespread clustering, notably favouring closing prices ending in zero. Multivariate analysis explores the impact of firm size, price level, volatility, and turnover on clustering. Results reveal pervasive clustering, strengthening with higher prices and turnover but weakening with larger trade volumes, firm size, and smaller tick sizes. These empirical findings support the theoretical expectations of price negotiation and resolution hypotheses.

The observed clustering presents an opportunity for investors to potentially capitalize on this market anomaly and achieve supra-normal returns.

Price clustering, the phenomenon where certain price levels are traded more frequently, challenges the efficient market hypothesis and has been extensively studied in financial markets. However, the Scandinavian stock markets, particularly those in the Nasdaq Nordic Exchange, remain unexplored in this context.

The purpose of this study is to use the grounded theory to summarize the types of celebrity persona and to construct a theoretical model for celebrity persona on consumer purchase intention. Based on the study results, it provides better suggestions for merchants and live streamers and is an expansion of previous research on live-streaming e-commerce.

The grounded theory is recognized as the most scientific qualitative research method and is the ideal explorative method for generating theory. First, the participants were interviewed, and interview data were collected. Then the interview data were organized and analyzed. Finally, this paper summarizes the types of celebrity persona and constructes a theoretical model framework of celebrity persona on consumers' purchase intention.

The results show that the celebrity live streamer persona can be divided into two types: personalized persona and professional persona. Through emotional attachment, the celebrity's persona affects the consumer's purchase intentions. As well as, product type plays a moderating role between celebrity persona and consumer purchase intentions.

The contribution of this research is to start from the celebrity persona, link the celebrity persona with the consumer purchase intentions and expand the research scope of the celebrity persona. It opens the “black box” of the heterogeneity of celebrity live streamers' characteristics on consumer purchase intentions.

Prior research seldom explores the different structures of marketing presence in the top management team (MPTMT) and their impact on new product performance. In this paper, we distinguish among three structures of MPTMT: (1) a dedicated MPTMT; (2) a joint marketing and sales MPTMT; and (3) a joint marketing and other operations MPTMT. We then examine how these three structures of MPTMT are related to cross-functional integration in NPD and, subsequently, new product performance.

Path analysis is used to test the model using data collected from 139 U.S. manufacturing firms. We conducted two rounds of survey data collection (with a one-year gap) to assess the potential effect of common method variance.

The results show that, compared with no MPTMT, all MPTMT structures positively affect cross-functional integration in NPD, which, in turn, enhances new product performance. However, joint MPTMT structures have a greater impact than a dedicated MPTMT. Our moderation analysis also reveals that as TMT heterogeneity increases, the effect of dedicated MPTMT diminishes, but the effects of the other two joint structures remain positive and stable.

The model could include alternative mediating organizational processes and performance outcomes.

The findings provide managers with insight on how to configure and leverage marketing influence in the upper echelons in both SMEs and large firms.

The findings of this study highlight the importance of delineating MPTMT structures, understanding how they create value, and specifying their boundary conditions.

This study aims to explore the drivers (i.e. service innovation, service exchange, customer wellbeing and employee wellbeing) and organizational culture in the service ecosystem in the hospitality sector.

This study adopted a quantitative approach by collecting data from employees and customers of the top 10 hotels (identified from three major websites, i.e. Goibibo, Trivago and MakeMyTrip) functional in Jammu city, North India. Exploratory factor analysis, confirmatory factor analysis and partial least square analysis are used to analyse the data.

The study findings reveal that among the four drivers (i.e., service innovation, service exchange, employee wellbeing and customer wellbeing) customer wellbeing shows a strong impact and significant impact on the service ecosystem. Following this, the study also exhibits that organizational culture significantly moderates the relationship between service innovation and the service ecosystem. However, it does not show any moderating influence among the other drivers of the service ecosystem.

This study is conducted only in the top 10 hotels (three and four stars) of Jammu city, North India, which might not represent all Indian hotels.

The study contributes by establishing the role of four service ecosystem drivers, namely service innovation, service exchange, employee wellbeing and customer wellbeing. Following this, the study empirically tested and validated the service ecosystem framework in the context of north Indian hotels. The study also establishes the significant role of organizational culture, particularly group culture and hierarchy culture, in strengthening the service ecosystem.

Servitization of products is becoming increasingly prevalent among manufacturing enterprises. Existing research has primarily focused on exploring whether the direct impact of servitization on manufacturer performance follows a linear or a curvilinear relationship. However, the understanding of the underlying mechanisms between servitization and manufacturer financial performance remains limited. This paper aims to examine the non-linear relationship between servitization and manufacturer performance as well as the mediating process and boundary condition associated with this relationship.

Drawing on resource-advantage theory, this paper proposes a theoretical model of the U-shaped relationship between servitization and the financial performance of equipment manufacturers. Panel data of 248 listed equipment manufacturers in China during the period of 2010–2020 are used to test each hypothesis through the ordinary least square method.

The empirical results indicate that servitization follows a U-shaped relationship with service business focus and the financial performance of equipment manufacturers. Service business focus mediates this U-shaped relationship between servitization and financial performance, and digital technology application moderates this relationship.

This paper pioneers the unraveling of the potential mechanism that can explain the curvilinear relationship between servitization of manufacturers and financial performance. This mechanism is the focus of the service business, which is theoretically delineated and empirically tested. Furthermore, digital technology application enables manufacturers to achieve service business focus more effectively in the process of servitization. Thus, this study addresses the call for research on digital servitization.