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The business landscapes in Asia and Africa are predominantly characterized by small and medium enterprises (SMEs) facing significant resource constraints. Understanding the capability dynamics of these enterprises in such contexts carries significant implications for theory and practice. This paper aims to addresses a crucial question of whether increasing customer involvement capability consistently yields the necessary rent for enterprises operating under resource constraints in emerging markets in Asia and Africa. By investigating this question, the paper offers SMEs a more nuanced approach to capability development, enabling them to achieve better returns on their investments.

To ensure the robustness of the findings, data were collected from SME service firms operating in two emerging economies: India (Asia) and Ghana (Africa). Data were collected in two waves to allow for catering to specific environmental conditions not accounted for in the study. Two-stage data analysis was then conducted to test the hypothesized relationships across the two countries.

The findings reveal that customer involvement capability does not always lead to an increase in firm-level competitiveness, and the effect follows an inverted U-shaped pattern. However, the nature of this relationship varies under different market conditions in both contexts. Specifically, in periods of low customer demand and intense competition, the relationship is linear and positive. On the other hand, in periods of high demand and competition, the relationship becomes inverted U-shaped, returning to a direct relationship with firm-level competitiveness.

This paper provides a resolution to the critical issue of whether customer involvement capability consistently delivers firm performance benefits, particularly for resource-constrained SMEs in emerging markets. By explaining how SMEs in emerging markets can fully capitalize on their capability development to optimize their resources, this paper makes a distinctive contribution. Moreover, it sheds light on the importance of aligning involvement capabilities with prevailing market conditions for SMEs to reap the maximum benefits.

The purpose of this paper is to explore the perceived benefits of integrated reporting (IR) and factors influencing the motives that supervisory board members (SBMs) have for advocating a change towards IR implementation.

An exploratory survey study was conducted to investigate the influence of external market conditions, internal organizational conditions and observed benefits on the motivation to advocate IR adoption in companies that have not yet implemented IR. A unique set of survey data from 62 SBMs of Dutch companies was used for analysing the propositions derived from IR literature and based on institutional theory, legitimacy theory and diffusion of innovation theory.

The respondents indicated to be supportive of IR adoption. SBMs who had experienced the implementation of IR observed that IR offers benefits. Their motives for advocating a change towards IR in companies that had not implemented IR were influenced most by the observed benefits in IR companies. SBMs only involved in companies that had not adopted IR are motivated to support IR adoption to a similar extent. These findings suggest that directly observed benefits by SBMs need to exceed a considerable minimum level before these SBMs are more motived to advocate IR than their peers who have not witnessed the implementation of IR and that experiences are shared across companies. The motivation of both groups is influenced by external market conditions but not by internal organizational conditions.

The findings have implications for potential IR adopters and institutions promoting the further diffusion of IR as they emphasize the need for tangible benefits of IR and confirm that sharing good practices and benefits of IR can provide a catalyst for IR adoption. The findings contribute to the understanding of the motivation of SBMs as an important organizational condition for implementing IR as this study provides insights in the factors that drive this motivation of key actors influencing the decision to implement IR. Furthermore, the finding that these factors predominantly comprise tangible results and external market conditions is relevant from an organizational change perspective.

Understanding the mechanisms of IR-adoption decisions provides a relevant basis for deploying programmes promoting IR as a general reporting standard. This could provide society and a broad range of stakeholders with access to information incorporated in integrated reports. It could ultimately have a major impact on society by improving decision-making and increasing the long-term sustainability of organizations and their relations with stakeholders.

This study provides preliminary empirical evidence concerning the perspectives of SBMs on their motives for advocating IR, based on a unique sample from a country that has been involved with IR from its start.

The purpose of this paper is to examine whether Fama–French common risk-factor portfolio investors herd on a daily basis for five developed markets, namely, Europe, Japan, Asia Pacific ex Japan, North America and Globe.

To examine the herd behavior of common risk-factor portfolio investors, this paper utilizes the cross-sectional absolute deviations (CSAD) methodology, covering a daily data sampling period of July 1990 to January 2019 from Kenneth R. French-Data Library. CSAD driven by fundamental and non-fundamental information is assessed using Fama–French five-factor model.

The results do not provide evidence for herding under normal market conditions, either when reacting to fundamental information or non-fundamental information, for any region under consideration. However, Fama–French common risk-factor portfolio investors mimic the underlying risk factors in returns related to size and book-to-market value, size and operating profitability, size and investment and size and momentum of the equity stocks in European and Japanese markets during crisis period. Also, no considerable evidence is found for herding (on fundamental information) under crisis and up-market conditions except for Japan. Ancillary findings are discussed under conclusion.

Further research on new risk factors explaining stock return variation may help improve the model performance. The performance can be improved by adding new risk factors that are free from behavioral bias but significant in explaining common stock return variation. Also, it is necessary to revisit the existing common risk factors in order to understand behavioral aspects that may affect cost of capital calculations (e.g. pricing errors) and valuation of investment portfolios.

This is the first paper that examines the herd behavior (fundamental and non-fundamental) of Fama–French common risk-factor investors using five-factor model.

This study aims to investigate the market timing strategy in different market conditions (i.e. up, down, normal and in-financial-crisis situation) in the emerging market of Pakistan over the period 1995 to 2015. Furthermore, this study tests the validity of the capital asset pricing model (CAPM) and Fama and French model.

This study considers monthly stock returns of 167 firms and constructs six different portfolios on the basis of different size and book to market ratio. The Treynor and Mazuy model is used to capture the market timing strategy.

The results indicate evidence of the market timing in normal market conditions. However, there is less supportive evidence of market timing in up-market, down-market and in-financial-crisis situations. This study also confirms the validity of the capital asset pricing model and Fama and French three-factor model with strong support of value premium and size premium in the stock market.

The findings of this study are helpful to companies in estimating the cost of issuing equity more accurately. The investors can use market timing to make their investment in a more better and profitable manner.

Unlike other previous studies, this study considers an extended period to test the validity of the capital asset pricing model and Fama and French model. In addition, this study is novel in testing the marketing timing of the firms in the context of emerging economy of Pakistan.

Stirred by scant regard for market phases in portfolio performance assessments, the current paper investigates the active versus passive investment strategies under the bull and bear market conditions in emerging markets focusing on South Africa as a case study.

Methodologically, the measures of Jensen's alpha and Treynor index are applied to the monthly returns of 20 funds from January 2010 to June 2022.

The results are enlightening; though they contradict developed market evidence, they are consistent with emerging market trends. The findings show that actively managed funds outperform the market benchmark and passive investing style under bear and normal market conditions. Passive investment strategy outperforms both market benchmark and actively investing style under bull market conditions.

In the face of improved market efficiency, increased liquidity and recent technological impact, the findings of this study have practical application. The study outcomes should inform and update global investors, especially asset managers interested in emerging markets; however, the limitations of the study should also be considered.

While limited studies consider market conditions when comparing and contrasting the performance of passive versus active investing, such consideration is lacking in emerging markets. The current study corrects this literature imbalance.

In this paper, the authors contribute with insights on competition and cooperation in multinational enterprises with a focus on challenges related to these governance mechanisms in a knowledge development context. The mechanisms have been widely recognized as important for developing knowledge, but their contradicting nature implies considerable complexity when it comes to governance. The complexity is further increased as a result of the headquarters-subsidiary relationships. The aim of this paper is to contribute with theoretical and empirical insights on these aspects by focusing on the research question: How and why does competition and cooperation in an MNE emerge over time?

A manufacturing MNE with headquarters (HQ) in Sweden is analyzed on both HQ and subsidiary levels. Interviews with 24 managers in Sweden and India have been performed.

The study illustrates that competition and cooperation are integral aspects in HQ-subsidiary relationships. The results show that both competition and cooperation depend on environmental, organizational and object-related conditions and that these conditions influence the dynamics of the interplay. The importance of including a subsidiary perspective and the interdependencies in an MNE setting are emphasized.

The authors add to the discussion on the interplay between competition and cooperation as they play an important role for knowledge development in MNEs. The results indicate that they do not take place simultaneously, and therefore, the authors suggest that the dynamic can be better understood by focusing on the interplay and analyze the concepts separately.

The purpose of this paper is to examine the financial factors across multiple levels of analysis that influence the performance effects of the unrelated diversification strategy, including institutional-, industry- and firm-levels.

Using a unique panel dataset of Italian firms from 1980 to 2010, the paper tests hypotheses on how industry external financial dependence and the firm's financial constraints both separately and jointly alter the performance benefits of unrelated diversification in contexts with financial market inefficiencies.

Unrelated diversification increases performance in weak financial contexts and such positive effect is enhanced by greater industry external financial dependence and greater firm financial constraints. However, as financial markets develop, the moderating effects of firm financial constraints shrink.

The study highlights the importance of recognizing the multiple financial contingencies that may alter the benefits of the unrelated diversification strategy, suggesting caution in its pursuit to boost firm performance.

The authors develop a theoretical framework that explains the performance outcomes of unrelated diversification, linking the benefits of an internal capital market (ICM) with the financial context of the firm and offering a fine-grained analysis that moves beyond the advanced/emerging economy dichotomy. Furthermore, leveraging on the unprecedented time frame of the empirical analysis, the paper highlights the crucial role of industry- and firm-level financial contingencies and demonstrates that their effects change at varying levels of development of the financial context.

The purpose of this pilot study was to identify the key factors that influence the decisions of entrepreneurs who are considering the creation of a new venture. The pilot was conducted to explore the cognitive antecedents of entrepreneurial decision-making and whether specific factors contribute to the decision to create a new venture.

The study utilised an inductive and interpretive research design within a constructivist paradigm. The sample comprised entrepreneurs situated in a business incubation unit who engaged in a series of semi-structured interviews. The results of this study will be used to refine the questions asked in preparation for a larger sample using in-depth interviews with identified entrepreneurs. The resulting narrative in this pilot was subjected to discourse analysis and is categorised into relevant themes.

The findings in this pilot study reveal that factors such as technological advancement, market opportunity, competition, customer demand and prevailing market conditions have a significant influence on the decision-making process involved in creating a new venture.

Although the pilot has identified several factors in entrepreneurial decision-making, further work will be needed in the research design to be able to expose the cognitive processes associated with each factor. The aim is to identify the common cognitive characteristics associated with thinking through the decision to create a new venture with a much larger sample of entrepreneurs.

The value of this research lies in exploring and developing a better understanding of the antecedent cognitive processes used by entrepreneurs for identifying unique, innovative new ideas and converting them into exploitable products or services through new venture creation.

The economic and administrative conditions of countries normatively have an effect on the economy and level of market development. Moreover, it is of great importance for a healthy economy whether the public institutions and organizations are transparent and functioning in accordance with their purpose. The aim of this study is to show whether there is a relationship between transparency and market efficiency.

Correlation analysis has been conducted between prediction accuracy rates, which are obtained by seven different machine learning algorithms and Corruption Perception Index (CPI) levels.

It has been statistically shown that the indices of countries with low corruption levels are harder to predict, which, in turn, can be interpreted as having higher weak-form market efficiency. According to that, an intermediate negative correlation has been found between CPI scores and predictability levels of stock indices. Considering the findings, it can be interpreted that the markets of countries with relatively more transparent and well-functioning public sector have more weak-form market efficiency.

The study can be extended with cutting-edge machine learning and deep learning techniques in future studies. There are very few studies which try to explain factors related to market efficiency. Thus, the authors claim that there is still room for further research in order to determine the factors related to market efficiency, implying that current literature is still far from explaining the causation behind the inefficiencies.

According to findings, the markets of countries with relatively more transparent and well-functioning public sector have more weak-form market efficiency. Based on these findings, in practice, it can be said that more successful predictions can be made using machine learning algorithms in countries with relatively lower CPI scores.

In literature, the factors related to market efficiency are still far from explaining the causation behind the inefficiencies. Thus, it has been investigated whether transparent and well-functioning public institutions and organizations have any relation with market efficiency.

This study aims to propose a comprehensive greenfield foreign direct investment (FDI) attractiveness index using exploratory factor analysis and automated machine learning (AML). We offer offer a robust empirical measurement of location-choice factors identified in the FDI literature through a novel method and provide a tool for assessing the countries' investment potential.

Based on five conceptual key sub-domains of FDI, We collected quantitative indicators in several databases with annual data ranging from 2006 to 2019. This study first run a factor analysis to identify the most important features. It then uses AML to assess the relative importance of each resultant factor and generate a calibrated index. AML computational algorithms minimize predictive errors, explore patterns in the data and make predictions in an empirically robust way.

Openness conditions and economic growth are the most relevant factors to attract FDI identified in the study. Luxembourg, Hong Kong, Singapore, Malta and Ireland are the top five countries with the highest overall greenfield attractiveness index. This study also presents specific indices for the three sectors: energy, financial services, information and communication technology (ICT) and electronics.

Existent indexes present deficiencies in conceptualization and measurement, lacking theoretical foundation, arbitrary selection of factors and use of limited linear models. This study’s index is developed in a robust three-stage process. The use of AML configures an advantage compared to traditional linear and additive models, as it selects the best model considering the predictive capacity of many models simultaneously.