Zhiwen Li

With the significant increase in users’ privacy awareness and strict regulatory response, user privacy protection faces a dilemma between platform operational flexibility and commercial potential. The personal data use authorization has become an important mechanism influencing platform data transactions and government regulation, thereby shaping the development trajectory of the data trading market. Previous literature has yet to fully elucidate the complex interactions and evolutionary equilibrium strategies among the parties involved in data transactions. This study builds an evolutionary game model involving three parties—users, platforms, and the government—to explore the evolutionary equilibrium of users’ personal data use authorization strategy, platforms’ data trading strategy, and the government’s regulatory strategy. The findings reveal that: (1) User authorization does not always promote platform data transactions. Under the personal data use authorization mechanism, user authorization facilitates platform data transactions only when either the data transaction price is low and the value of user behavioral data exceeds a certain threshold, or the data transaction price is high and the value of user behavioral data falls within a specific range. (2) User authorization is not a sufficient condition for the government to impose strict regulatory measures on platform data transactions. When the regulatory cost is low, the government’s strict regulatory strategy is influenced by both the data transaction price and the value of user behavioral data. Specifically, under low-price–medium-value or high-price–high-value conditions, the government tends to strictly regulate platform data transactions when users do not authorize the use of personal data. Conversely, under low-price–high-value or high-price–medium-value conditions, the government is more inclined to enforce strict regulation when users authorize the use of personal data. This study contributes to evaluating the role of the personal data use authorization mechanism, offering valuable insights to platforms and the government on data transactions and regulation.

Antitrust authorities are concerned with the dominant market position of Tech Giants such as Google, Meta, or Amazon. These digital conglomerates are characterized by platform-based business models and multimarket contact (MMC). In traditional one-sided markets, theory and empirical evidence show that MMC tends to relax competition. In this paper, we revisit this result in the context of platform competition with competitive bottleneck and cross-market externalities, and provide new insights into the impact of MMC on platform competition. In this context, when platforms charge the two groups of users (bilateral pricing), we find that MMC always decreases the profitability of platforms regardless of the nature and magnitude of cross-market externalities. Then we consider the case in which platforms can only charge one group of users (unilateral pricing). When platforms charge the side on which they are not directly competing for users (i.e. the side that is not the competitive bottleneck), MMC may relax competition only if cross-group externalities and cross-market externalities are both sufficiently small. From a competition policy perspective, our paper provides insights into how antitrust authorities should review conglomerate mergers in digital markets and assesses the effects of the diversification strategies of digital platforms in the context of cross-market externalities and competitive bottleneck.

The traditional agricultural economic systems, mainly in developing nations, faces various challenges including reduction in cultivated land, decreasing crop productivity, declining groundwater levels, changing pest and disease patterns, and overall climate variability. Adapting to these modifications requires considering different factors, including the information and communication technologies (ICTs). Yet, these factors and their impact remain untapped for smart farming. The representative sample of 300 farmers were chosen by using a simple random sampling technique from villages of Lahore and Multan Pakistan. The multinomial logit regression method was used to identify the determinants of ICTs adoption in agriculture. The research findings highlighted that the education level of farmers, farmers’ association, compatibility of innovation, relative advantage of technology, observability of technological innovation, access to agricultural extension services, capacity building initiatives, and access to AI tools were promoting farmers’ digital inclusion in agriculture significantly. Absolutely, initiating awareness campaigns and capacity building programs with the collaborative efforts of agricultural extension and advisory service departments may be highly effective for fostering understanding among small landholders regarding the significance of ICTs in agriculture. Access to agricultural extension services is crucial for enabling the farming community to make informed decisions about crop cultivation, discover new market opportunities, and adopt new information and communication technologies. Moreover, the study suggested that government officials, policy makers, farmers, and agricultural organizations should emphasized on these attributes while advocating for sustainable digital agricultural practices to promote the welfare of small landholders and rural development.

As the e-commerce landscape diversifies, suppliers are faced with the critical decision of how to effectively launch their products through e-commerce channels with varying business models. This study aims to explore the strategic considerations for a supplier launching products through two distinct e-commerce channels: one based on a direct sale model and the other on a reselling model. It builds a theoretical model to examine the supplier’s decision-making across three strategic options: a simultaneous launch through both channels, a sequential launch starting with the direct sale model followed by the reselling model, and vice versa. The equilibria of those options are derived through game analysis and further compared. The results reveal that for suppliers under a non-alliance pricing contract, a simultaneous product launch across both channels is the most advantageous approach. Conversely, in scenarios where an alliance pricing contract is in place, the optimal strategy shifts towards a sequential launch. The decision of which channel to ally with—whether the direct sale or the reselling model—hinges critically on the difference in service efficiency and the intensity of competition between the channels. This nuanced analysis highlights the importance of strategic flexibility and alignment with channel dynamics in maximizing product launch success in the evolving e-commerce environment.

This research work estimated technical efficiency (TE), allocative efficiency (AE) and economic efficiency (EE) of cereal crops and identified the determinants of technical inefficiency of rice-wheat farming system. Primary data was collected from 120 farmers in Sheikhupura district, Pakistan randomly. For this purpose, a non-parametric Data Envelopment Analysis (DEA) technique was applied. Tobit regression model was estimated to investigate determinants of technical inefficiency of the system. The results revealed that TE, AE, and EE of rice farmers were 0.81, 0.61, and 0.50, respectively. The results revealed that TE, AE, and EE of wheat farmers were 0.87, 0.80, and 0.70, respectively. The investigation shows that if wheat farmers operated at a full efficiency level, they could reduce their input use by 13% and reduce cost by 20% without reduction in output and with existing technology (modified agricultural and information and communication technology).

Entrepreneurial orientation has recently been touted as a tool for solving enterprise failures in emerged and emerging economies especially during and after an epidemic. This study aims at understanding the impact of entrepreneurial orientation on enterprise performance in the Ghanaian food processing industry by assessing the mediating effects of innovation types and intellectual property. Data were collected from 702 owners/managers in the food processing industry via survey questionnaires. The data were analyzed using the partial least squares structural equation modeling (PLS-SEM) to test the hypothesis via the Smart PLS software. The findings show that entrepreneurial orientation, innovation types, and intellectual property positively and significantly influenced enterprise performance. Furthermore, the results indicated that the mediation effects of innovation types and intellectual property were full and partial, respectively. Useful policy implications are further proposed and discussed based on the study results.

Reductions in search costs are generally found to increase efficiency and welfare. Using a simple search model we show that when an upstream firm incurs a search cost to identify a potential trading partner and the two parties then negotiate the wholesale price, a reduction in search cost can actually reduce welfare. Furthermore, in a market driven by seller search, a search cost of zero is never socially optimal.