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The purpose of this study is to investigate the structure and dynamics of academic articles relating to public procurement (PP) in the period 1984–2022 (up to May). The researchers also intend to analyse how this knowledge domain has grown since 1984.

A bibliometric analysis was carried out to examine the existing state of PP research. Based on 640 journal articles indexed in the Scopus database and written by 1,247 authors over nearly four decades, a bibliometric analysis was conducted to reveal the intellectual structure of academic works pertaining to PP.

Findings reveal that PP research from Scopus has significantly increased in the past decade. Major journals publishing PP research are International Journal of Procurement Management, Journal of Cleaner Production, Journal of Purchasing and Supply Management and Public Money and Management. Results also indicate that authors’ cooperation network is fragmented, showing limited collaboration among PP researchers. In addition, results suggest that the institutional collaboration network in PP research mirrors what is commonly referred to as the North–South divide, signifying insufficient research collaboration between developed and developing countries’ institutions. According to the co-occurrence keyword network and topic modelling, PP revolves around five main themes, including innovation, corruption, sustainable and green PP, PP contracts and small and medium enterprises. Based on these results, several directions for future research are suggested.

This paper provides an increased understanding of the entire PP field and the potential research directions.

To the best of the authors’ knowledge, this study is the first-ever application of bibliometric techniques and topic modelling to examine the development of PP research since 1984 based on scholarly publications extracted from the Scopus database.

Innovation is regarded as a crucial determinant of growth and development in South Africa, and small, medium and micro enterprises (SMMEs) have been earmarked as instruments for the achievement of the socio-economic goals and innovation as set out in the National Development Plan. The purpose of this study is to investigate the effect of innovation on SMME performance in South Africa.

The empirical analysis was conducted using the quantile regression technique to examine the effect of innovation on the performance of firms at different sales levels. Data from the World Bank's enterprise survey was used for the analysis.

The results of the empirical analysis showed that R & D expenditures have a positive and significant effect on performance for firms with higher sales (high growth or larger firms). There is evidence that the introduction of new products/services promotes performance for low growth/ smaller firms.

The empirical results imply that innovation is crucial for SMMEs’ development and growth. However, smaller/low growth firms are not able to spend on R & D due to a lack of funds which could be the reason for their low survival rate. More support needs to be provided to smaller firms with lower sales growth, given the large financial outlay required for R & D expenditures. Despite the lack of funding for R & D expenditure, smaller firms are encouraged to introduce new products and methods of production that do not require major financial outlays.

There is scant empirical evidence on the impact of innovation on firm performance in South Africa. Most studies investigate the challenges faced by SMMEs and the different types of innovation approaches used by firms. Furthermore, the study employs the quantile regression approach which highlights the effect of innovation on firms of different sizes.

The authors examine the role of analysts’ prior experience of forecasting for firms exposed to epidemics on analysts’ forecast accuracy during the COVID-19 pandemic.

The authors examine the impact of analysts’ prior epidemic experience on forecast accuracy by comparing the changes from the pre-COVID-19 period (calendar year 2019) to the post-COVID period extending up to March 2023 across HRE versus non-HRE analysts. The authors consider a full sample (194,980) and a sub-sample (136,836) approach to distinguish “Recent” forecasts from “All” forecasts (including revisions).

The study's findings reveal that forecast accuracy for HRE analysts is significantly higher than that for non-HRE analysts during COVID-19. Specifically, forecast errors significantly decrease by 0.6% and 0.15% for the “Recent” and “All” forecast samples, respectively. This finding suggests that analysts’ prior epidemic experience leads to an enhanced ability to assess the uncertainty around the epidemic, thereby translating to higher forecast accuracy.

The finding that the expertise developed through an experience of following high-risk firms in the past enhances analysts’ performance during the pandemic sheds light on a key differentiator that partially explains the systematic difference in performance across analysts. The authors also show that industry experience alone is not useful in improving forecast accuracy during a pandemic – prior experience of tracking firms during epidemics adds incremental accuracy to analysts’ forecasts during pandemics such as COVID-19.

The study findings should prompt macroeconomic policymakers at the national level, such as the central banks of countries, to include past epidemic experiences as a key determinant when forecasting the economic outlook and making policy-related decisions. Moreover, practitioners and advisory firms can improve the earning prediction models by placing more weight on pandemic-adjusted forecasts made by analysts with past epidemic experience.

The uncertainty induced by the COVID-19 pandemic increases uncertainty in global financial markets. Under such circumstances, the importance of analysts’ role as information intermediaries gains even more importance. This raises the question of what determines analysts’ forecast accuracy during the COVID-19 pandemic. Building upon prior literature on the role of analyst experience in shaping analysts’ forecasts, the authors examine whether experience in tracking firms exposed to prior epidemics allows analysts to forecast more accurately during COVID-19. The authors find that analysts who have experience in forecasting for firms with high exposure to epidemics (H1N1, Zika, Ebola, and SARS) exhibit higher accuracy than analysts who lack such experience. Further, this effect of experience on forecast accuracy is more pronounced while forecasting for firms with higher exposure to the risk of COVID-19 and for firms with a poor ex-ante informational environment.

After the COVID-19 outbreak, the Federal Reserve has undertaken several monetary policies to alleviate the pandemic consequences on the stock markets leading to a misunderstanding on the cryptocurrency market response. This paper aims to evaluate the effects of the Federal Reserve monetary policy on the Islamic and conventional cryptocurrency dynamics during the COVID-19 pandemic. We, specifically, examine the associate bubbles and feedbacks effects.

This paper developed a novel methodology that detects market bubbles using the statistical indicators defined by Psychological (PSY) tests. It also investigated the effect of the Federal Open Market Committee (FOMC) announcements on conventional and Islamic cryptocurrencies compatible with Islamic laws “Shari’ah” by using the event-driven regression.

The empirical results show that the FOMC announcements have a positive significant effect after one day of the event and a negative effect before two days of the announcement on the conventional cryptocurrency markets. However, the reaction of Islamic cryptocurrencies to these events is not significant except for Hello Gold after one day of the announcement. Besides, the Hello Gold and X8X cryptocurrencies present no bubbles during this period. However, Bitcoin and Ethereum markets have short-lived bubbles.

The main contribution of this study is the investigation of the response and vulnerability to pandemic shocks of a new category of cryptocurrencies backed by tangible assets. This work has practical implications as it provides new insights into trading opportunities and market reactions.

To our knowledge, this work is the first study that compares the response of Islamic and conventional cryptocurrency markets to FOMC announcements during the COVID-19 pandemic and examines the presence of bubbles in these markets. Besides, the originality of this work is derived from the novelty of the data employed and the method used (PSY tests) in this study.

The purpose of this study is to examine whether and how analysts’ foreign ancestral origins would have an effect on analysts’ earning forecasts in particular and ultimately on firms’ information environment in general.

By inferring analysts’ ancestral countries based on their surnames, this study empirically examines whether analysts’ ancestral countries affect their earnings forecast errors.

Using novel data on analysts’ foreign ancestral origins from more than 110 countries, this study finds that relative to analysts with common American surnames, analysts with common foreign surnames tend to have higher earnings forecast errors. The positive relation between analyst foreign surnames and earnings forecast errors is more likely to be observed for African-American analysts and analysts whose ancestry countries are geographically apart from the USA. In contrast, this study finds that when analysts’ foreign countries of ancestry are aligned with that of the CEOs, analysts exhibit lower earnings forecast errors relative to analysts with common American surnames. More importantly, the results show that firms followed by more analysts with foreign surnames tend to exhibit higher earnings forecast errors.

Taken together, findings of this study are consistent with the conjecture that geographical, social and ethnical proximity between managers and analysts affect firms’ information environment. Therefore, this study contributes to the determinants of analysts’ earnings forecast errors and adds to the literature on firms’ information environment.

This study examines the roles of cross-sectional dependence, asymmetric structure and country-to-country policy variations in the inflation-poverty reduction causal nexus in selected sub-Saharan African (SSA) countries from 1981 to 2019.

To account for cross-sectional dependence, heterogeneity and policy variations across countries in the inflation-poverty reduction causal nexus, this study uses robust Hatemi-J data decomposition procedures and a battery of second-generation techniques. These techniques include cross-sectional dependency tests, panel unit root tests, slope homogeneity tests and the Dumitrescu-Hurlin panel Granger non-causality approach.

Unlike existing studies, the panel and country-specific findings exhibit several dimensions of asymmetric causality in the inflation-poverty nexus. Positive inflationary shocks Granger-causes poverty reduction through investment and employment opportunities that benefit the impoverished in SSA. These findings align with country-specific analyses of Botswana, Cameroon, Gabon, Mauritania, South Africa and Togo. Also, a decline in poverty causes inflation to increase in the Congo Republic, Madagascar, Nigeria, Senegal and Togo. All panel and country-specific analyses reveal at least one dimension of asymmetric causality or another.

All stakeholders and policymakers must pay adequate attention to issues of asymmetric structures, nonlinearities and country-to-country policy variations to address country-specific issues and the socioeconomic problems in the probable causal nexus between the high incidence of extreme poverty and double-digit inflation rates in most SSA countries.

Studies on the inflation-poverty nexus are not uncommon in economic literature. Most existing studies focus on inflation’s effect on poverty. Existing studies that examine the inflation-poverty causal relationship covertly assume no asymmetric structure and nonlinearity. Also, the issues of cross-sectional dependence and heterogeneity are unexplored in the causal link in existing studies. All panel studies covertly impose homogeneous policies on countries in the causality. This study relaxes this supposition by allowing policies to vary across countries in the panel framework. Thus, this study makes three-dimensional contributions to increasing understanding of the inflation-poverty nexus.

The COVID-19 pandemic, which appeared in China in late 2019, has affected the world psychologically, socially and economically in 2020. Tourism is one of the areas where the effects of COVID-19 have been felt most clearly. The study aims to determine the effect of negative problem orientation (NPO) and perceived risk related to the COVID-19 pandemic on travel and destination visit intention.

This study employed a convenience and probabilistic sampling method for collecting data from 531 respondents using an online questionnaire. Partial least square structural equation modeling (PLS-SEM) was used for testing research model.

According to the findings, NPO and perceived risk related to the pandemic were found to have direct and indirect effects on the travel behavior of tourists. The results of this research provide theoretical and practical implications for hospitality and travel businesses on topics such as the psychological effects of the pandemic and the travel behaviors of tourists.

It is estimated that the pandemic will also affect tourist behavior due to its effects on human psychology. For this reason, a study conducted in the context of tourist behavior theories is expected to contribute to the literature, managers and future of the tourism.

This paper aims to investigate the interplay of memorable tourism experiences (MTE) dimensions in driving behavioral intentions of heritage tourists through the mediating role of satisfaction.

Empirical data were collected from tourists in the heritage city of Kashan, Iran. Partial least squares-structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) were applied to analyze the data.

The results of PLS-SEM showed that three dimensions of MTE as follows: local culture, involvement and knowledge, significantly directly or indirectly influence tourists’ behavioral intention toward a destination. However, the results of fsQCA identified greater heterogeneity among the respondents by highlighting the positive effects of hedonism and novelty on satisfaction and revisit and word-of-mouth intentions.

This study enriches the empirical evidence on MTE by constructing a composite picture of the memorability of tourists’ experiences within a heritage tourism context. This study is one of the first to investigate the effects of dimensions of MTE on behavioral intentions using both symmetric (PLS-SEM) and asymmetric approaches to identify the more significant dimensions of MTE, as well as sufficient combinations of dimensions to predict behavioral intentions.

本文旨在研究难忘旅游体验 (MTE) 各维度通过满意度这个中介变量来驱动遗产旅游游客行为意图的机制

实证数据是从伊朗遗产城市卡尚的游客那里收集的。本研究采用偏最小二乘结构方程模型（PLS-SEM）和模糊集定性比较分析（fsQCA）对数据进行分析

偏最小二乘结构方程模型的研究结果表明，难忘旅游体验（MTE）的三个维度：当地文化、参与度和熟悉程度，显著地直接或间接地影响游客对目的地的行为意向。然而，模糊集定性比较分析的研究结果表明受访者间存在更大的异质性，其结果凸显了享乐主义和新鲜感对满意度、重游意向和口碑(WOM)意向的正效应

本研究通过构建遗产旅游背景下游客体验难忘性的相互影响机制，丰富了关于难忘旅游体验（MTE）的实证研究证据。本研究是第一个同时使用对称方法（PLS-SEM）和非对称方法（fsQCA）来探究MTE各维度对行为意向的影响的研究之一，通过这种方式可以识别出MTE各维度中更为重要的维度以及维度组合，以此来预测行为意向

Este artículo investiga la influencia de las dimensiones de las experiencias turísticas memorables (ETM) en el fomento de las intenciones de comportamiento de los turistas del patrimonio a través del papel mediador de la satisfacción.

Se recogieron datos empíricos de turistas en la ciudad patrimonial de Kashan, Irán. Para analizar los datos se aplicaron las técnicas partial least squares – structural equation modeling (PLS-SEM) y fuzzy-set qualitative comparative analysis (fsQCA).

Los resultados que proporcionó el análisis PLS-SEM mostraron que tres dimensiones de las ETM: cultura local, implicación y conocimiento, influyen significativamente, de forma directa o indirecta, en la intención de comportamiento de los turistas hacia un destino. Sin embargo, los resultados del enfoque fsQCA identificaron una mayor heterogeneidad entre los encuestados al destacar los efectos positivos del hedonismo y la novedad sobre la satisfacción y las intenciones tanto de volver a visitar el destino como de realizar una comunicación de boca a boca (WOM).

Este estudio enriquece la evidencia empírica sobre las ETM al construir una imagen combinada del carácter memorable de las experiencias de los turistas dentro de un contexto de turismo patrimonial. Este estudio es uno de los primeros en investigar los efectos de las dimensiones las ETM en las intenciones de comportamiento utilizando enfoques simétricos (PLS-SEM) y asimétricos para identificar las dimensiones más significativas las ETM, así como para determinar las combinaciones necesarias de dimensiones para predecir las intenciones de comportamiento.

Metaverse, that is extended reality (XR)-based technologies such as augmented reality (AR) and virtual reality (VR), are increasingly believed to facilitate fundamental human practice in the future. One of the vanguards of this development has been the consumption domain, where the multi-modal and multi-sensory technology-mediated immersion is expected to enrich consumers' experience. However, it remains unclear whether these expectations have been warranted in reality and whether, rather than enhancing the experience, metaverse technologies inhibit the functioning and experience, such as cognitive functioning and experience.

This study utilizes a 2 (VR: yes vs no) × 2 (AR: yes vs no) between-subjects laboratory experiment. A total of 159 student participants are randomly assigned to one condition — a brick-and-mortar store, a VR store, an AR store and an augmented virtuality (AV) store — to complete a typical shopping task. Four spatial attention indicators — visit shift, duration shift, visit variation and duration variation — are compared based on attention allocation data converted from head movements extracted from recorded videos during the experiments.

This study identifies three essential effects of XR technologies on consumers' spatial attention allocation: the inattention effect, acceleration effect and imbalance effect. Specifically, the inattention effect (the attentional visit shift from showcased products to the environmental periphery) appears when VR or AR technology is applied to virtualize the store and disappears when AR and VR are used together. The acceleration effect (the attentional duration shift from showcased products to the environmental periphery) exists in the VR store. Additionally, AR causes an imbalance effect (the attentional duration variation increases horizontally among the showcased products).

This study provides valuable empirical evidence of how VR and AR influence consumers' spatial bias in attention allocation, filling the research gap on cognitive function in the metaverse. This study also provides practical guidelines for retailers and XR designers and developers.

Buying companies in the food industry increasingly recognize the need to cultivate relationships with their suppliers. Social capital and power are important to understand buyer–supplier relationships. Maintaining these relationships appears highly dependent on the degree of information sharing.

The study investigates how power and social capital dimensions are related to information sharing. A survey of first-tier suppliers in the Dutch meat processing industry was carried out. The data from 82 suppliers was analyzed using partial least squares.

It appears that expert power contributes to the cognitive and structural social capital. In contrast, coercive power showed no influence at all. Cognitive and structural social capital dimensions have a direct link to relational social capital, which significantly improves buyer–supplier information sharing in the food industry.

Buying companies can encourage supplier information sharing by building up their own expertise and cultivating social relationships. They should refrain from strong-handed practices.

Companies in the food and food processing industry are dependent on effective information exchange for their very survival. This study investigates the role of power and social capital in making such exchange possible and sustainable.