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As a response to global population growth and increasing demand for food, farmers have been complementing traditional agriculture practices with vertical farming (VF) and indoor hydroponic systems. To facilitate the growth of the VF industry, this paper aims to identify business model elements and their configurations that lead to high firm performance.

The research goals were met by conducting literature reviews coupled with a fuzzy-set qualitative comparative analysis (fsQCA) on five business model elements, “superior” OR “strong” performance as two possible outcomes, and the top-ranked global VF growers listed in the Crunchbase Database.

From the fsQCA results, it was observed that several business model configurations lead to strong firm performance. Vertical farms growing in urban settings and having strong customer engagement platforms, coupled with a presence of business-to-business (B2B) sales channels, are more consistently associated with superior performance. These results imply that the decision configuration of location, along with customer engagement activity and sales activity are differentiating factors between good firm performance and superior firm performance in the case of vertical farms.

This paper contributes to expanding the knowledge of business model theory, business model configurations and VF management, providing specific guidelines for vertical farm owners and investors related to decision-making for higher firm performance, as well as positive environmental, social and economic impact.

This paper analyses and assesses the effect of firm-specific determinants (FSDs) on supply-chain performance (SCP) and export performance (EP). It examines SCP’s influence on EP and its mediating effect on the relationship between FSD and EP.

This paper develops a theoretical framework based on the resource-based view (RBV) and dynamic-capability theory to understand SCP’s role in the FSD-EP link while empirically validating using the Indian automobile industry segments (IAIS) data. The sample frame comprises all listed firms in IAIS between the financial year 2010-11 and 2021–22, with continuous data availability throughout the considered timeline. The paper employs factor analysis for dimension reduction, a panel-data-fixed-effect model to analyze the relationships, bootstrap to test the mediation effect and focus-group discussion for validating the results obtained through statistical analyses.

FSD directly influences SCP’s efficiency aspect and EP. Distribution efficiency and inventory efficiency characteristics of SCP directly impact EP and completely mediate the relationship between FSD and EP.

This study provides significant insights into how firms can increase EP by focusing on firm-specific and SCP-related factors. To improve EP, firms should concentrate on enhancing distribution and inventory efficiencies. Firms must focus on critical firm-level factors like age, size and raw-material import capability to increase their ability to solve SC-specific barriers and improve SCP, resulting in enhanced exports.

This study investigates the impacts of FSD on SCP and EP and examines the mediating effect of SCP on the relationship between FSD and EP. Such a mediating role of SCP has rarely been probed in the literature.

Knowledge sharing enables a firm’s absorptive capacity to reconfigure its dynamic capabilities to sense, track and recognise embryonic business opportunities. Entrepreneurial opportunity recognition triggers entrepreneurs to invest in and upgrade their knowledge practices to improve entrepreneurial performance. This study aims to examine the relationship between knowledge sharing and absorptive capacity on entrepreneurial orientation as well as the moderating effect of opportunity recognition and the mediating effect of absorptive capacity.

A quantitative cross-sectional research design was applied to data from Algerian small and medium-sized enterprise managers in middle- to top-management positions. The final analysis using smart PLS included 246 respondents.

Knowledge sharing positively influenced entrepreneurial orientation and absorptive capacity. In addition, the findings reveal that entrepreneurial orientation positively influences entrepreneurial performance, and opportunity recognition strengthens the relationship between entrepreneurial orientation and entrepreneurial performance. Entrepreneurial orientation and absorptive capacity have partial mediating effects.

This study focuses on how firms create and share developed knowledge to enable absorptive capacity to fit a level of entrepreneurial orientation. This study validates the vital impact of opportunity recognition as a leading motivation for entrepreneurial orientation. The results highlight an important area of research and suggest that firms should focus on knowledge sharing to boost entrepreneurial outcomes.

The notions of entrepreneurship, absorptive capacity and knowledge sharing are extended by building on dynamic capability theory. Knowledge sharing increases absorptive capacity, which drives superior entrepreneurial orientation outcomes.

This study investigated the relationships among big data analytics capability (BDAC), low-cost advantage, differentiation advantage, market and operational performance underpinning the resource-based view (RBV) and the entanglement view of sociomaterialism (EVS) theories.

A total of 191 responses from members of the Federation of Malaysian Manufacturers were analysed using a structural equation modelling approach.

This study has conclusively demonstrated that BDAC is indeed a resource bundle comprising human skills, tangible and intangible resources. This study found that BDAC positively influences competitive advantage and firm performance. The differentiation advantage was found to be a key factor in explaining market performance. Theoretically, both RBV and EVS could be used to link BDAC, differentiation advantage and market performance to explain superior firm performance.

First, the sample is restricted to the manufacturers in Malaysia. Second, a single independent variable, BDAC, is used as a higher-order capability to influence competitive advantage, and thus, superior firm performance. Third, this study uses a self-reported survey, which means that only one respondent from each firm answered the questions. Fourth, this study excludes the focused strategy as it aims to investigate the competitive strategy used in the broader industry environment, rather than in a specific segment pursuing a focused strategy.

First, BDAC is a valuable, rare, inimitable and non-substitutable tool for manufacturers to enhance their firm performance. Second, BDAC is crucial for manufacturing firms to reduce costs and differentiate themselves. Third, a low-cost advantage may not help manufacturers achieve greater market and operational performance.

The relationship among BDAC, low-cost advantage, differentiation advantage, market and operational performance within manufacturing industry is empirically tested.

Product returns are a major challenge for e-businesses as they involve huge logistical and operational costs. Therefore, it becomes crucial to predict returns in advance. This study aims to evaluate different genres of classifiers for product return chance prediction, and further optimizes the best performing model.

An e-commerce data set having categorical type attributes has been used for this study. Feature selection based on chi-square provides a selective features-set which is used as inputs for model building. Predictive models are attempted using individual classifiers, ensemble models and deep neural networks. For performance evaluation, 75:25 train/test split and 10-fold cross-validation strategies are used. To improve the predictability of the best performing classifier, hyperparameter tuning is performed using different optimization methods such as, random search, grid search, Bayesian approach and evolutionary models (genetic algorithm, differential evolution and particle swarm optimization).

A comparison of F1-scores revealed that the Bayesian approach outperformed all other optimization approaches in terms of accuracy. The predictability of the Bayesian-optimized model is further compared with that of other classifiers using experimental analysis. The Bayesian-optimized XGBoost model possessed superior performance, with accuracies of 77.80% and 70.35% for holdout and 10-fold cross-validation methods, respectively.

Given the anonymized data, the effects of individual attributes on outcomes could not be investigated in detail. The Bayesian-optimized predictive model may be used in decision support systems, enabling real-time prediction of returns and the implementation of preventive measures.

There are very few reported studies on predicting the chance of order return in e-businesses. To the best of the authors’ knowledge, this study is the first to compare different optimization methods and classifiers, demonstrating the superiority of the Bayesian-optimized XGBoost classification model for returns prediction.

Factor investment is booming in global asset management, especially environmental, social, and governance (ESG), dividend yield, and volatility factors. In this chapter, we use data from the US securities market from 2003 to 2019 to predict dividends and volatility factors through machine learning and historical data–based methods. After that, we utilize particle swarm optimization to construct the Markowitz portfolio with limits on the number of assets and weight restrictions. The empirical results show that that the prediction ability using XGBoost is superior to the historical factor investment method. Moreover, the investment performance of our portfolio with ESG, high-yield, and low-volatility factors outperforms baseline methods, especially the S&P 500 ETF.

From a target perspective, this paper aims to examine the impact of environmental, social and governance (ESG) performance on mergers and acquisitions (M&A) transaction valuations.

This paper uses a sample of 629 international transactions conducted between 2002 and 2020. Ordinary least squares (OLS) regression was applied by using ESG aggregate score and the three ESG pillars: environment, social and governance.

This paper finds that the ESG performance of targets has a negative and significant impact on acquisition premiums. However, this paper finds that targets receive lower premiums by increasing their ESG score, suggesting that targets would do better to focus on ESG to increase shareholder wealth. Thus, results of this paper support the view that ESG-focused firms create shareholder value through the M&A process. Furthermore, results of this paper indicate that environmental and social aspects of ESG drive the acquisition premium. The governance score does not seem to be related to acquisition premiums.

To the best of the authors’ knowledge, this study is the first study to assess whether ESG performance impacts the valuation of M&A transactions by decomposing ESG into its three components.

Grounded in the resource-based view of the firm, this study aims to examine the effects of goal orientation and the mindfulness of entrepreneurs on firm innovation capability and analyzes that capability’s subsequent impact on firm performance. The authors also analyze whether mindfulness interacts with goal orientation to intensify its effect on firm innovation capability.

Simple random sampling was used to obtain the sample of Thai firms listed in the Department of Business Development database (n = 304). The data analysis was done by using partial least square structural equation modeling.

Goal orientation and mindfulness are positively associated with firm innovation capability. The analysis also supports the interaction effect of goal orientation and mindfulness on firm innovation capability. Moreover, firm innovation capability is positively associated with firm performance.

Goal orientation and mindfulness should be considered two essential soft skills that entrepreneurs must develop to build up their firms’ innovation capability. Because entrepreneurs are the key drivers of economic growth and sustainable development, the government agencies responsible for the entrepreneurship development should consider goal orientation and mindfulness as parts of their entrepreneurship training program and development policy.

The finding about the interaction effect of goal orientation and mindfulness on firm innovation capability provides new evidence that was not documented in previous research. The authors clarify that these are entrepreneurial characteristics that could supplement each other to maximize the potential of entrepreneurs and strengthen the innovation capability of their firms.

This study underscores the critical importance of knowledge management (KM) in the context of small and medium entrepreneurial firms (SMEFs) that aim to leverage their organisational learning capability (OLC) to enhance their product innovation performance (PIP). Drawing on the foundations of resource-based and contingency theories, this study delves into the impact of OLC on SMEFs' PIP through the intermediary role of KM, focussing on an emerging economy perspective. Additionally, this investigation explores how market dynamism (MDY) moderates the indirect connection between OLC and PIP via KM.

The study involved 262 SMEFs in Ghana, with data analysis conducted using PROCESS macros in SPSS 23.0 and LISREL 8.50.

This study's findings underscore the mediating role of KM in shaping the relationship between OLC and PIP. Furthermore, they reveal that, particularly in high MDY environments, the link between KM and PIP through KM is significantly strengthened.

The study clarifies that responding to MDY's demands is a complementary managerial capability enabling firms to channel their KM activities to improve PIP. Effectively, understanding the relationship between MDY and KM could substantially influence the policies and strategies managers adopt to improve PIP for organisational growth and survival.

This study extends the OLC–PIP research and contributes to the growing literature by offering a strong account of how OLC influences PIP and the prevailing boundary conditions that impact the KM-PIP relationship.

The aim of the study was to analyze the performance of Black-Litterman (BL) portfolios using a views estimation procedure that simulates investor forecasts based on technical analysis.

Ibovespa, S&P500, Bitcoin and interbank deposit rate (IDR) indexes were respectively considered proxies for the national, international, cryptocurrency and fixed income stock markets. Forecasts were made out of the sample aiming at incorporating them in the BL model, using several portfolio weighting methods from June 13, 2013 to August 30, 2022.

The Sharpe, Treynor and Omega ratios point out that the proposed model, considering only variable return assets, generates portfolios with performances superior to their traditionally calculated counterparts, with emphasis on the risk parity portfolio. Nonetheless, the inclusion of the IDR leads to performance losses, especially in scenarios with lower risk tolerance. And finally, given the impact of turnover, the naive portfolio was also detected as a viable alternative.

The results obtained can contribute to improve investors practices, specifically by validating both the performance improvement – when including foreign assets and cryptocurrencies –, and the application of the BL model for asset pricing.

The main contributions of the study are: performance analysis incorporating cryptocurrencies and international assets in an uncertain recent period; the use of a methodology to compute the views simulating the behavior of managers using technical analysis; and comparing the performance of portfolio management strategies based on the BL model, taking into account different levels of risk and uncertainty.