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The purpose of this study is shed light on the underlying forces behind entrepreneurship within a regional innovation system (RIS) in a remote rural region. The authors examine the following questions: Which are the main underlying forces behind the entrepreneurial process in a rural RIS characterized by traditionally low-tech, small-scale businesses? How can the development of a low-tech regional innovation system be conceptualized?

The design of the study is based on entrepreneurship theory. Data analysis followed practices used in phenomenography, a research approach used to analyse and identify commonalities and variations in populations' perceptions of a certain phenomenon. Data are composed using semi-structured interviews and a database composed of company information of all firms in the population.

A proactive mobilization of regional stakeholders and resources can be an important driving force behind the entrepreneurial process and generation of a rural RIS. Innovation can be generated within low-tech industries turning the rural context into an asset. An RIS in a remote rural context can be initiated and orchestrated by regional authorities, but knowledge brokering and orchestration can also be managed by networks of small-scale businesses brought together by mutual benefit and common interests.

Regional innovation systems theory is most often used to study high-tech industries. But by combining regional innovation systems with rural entrepreneurship and entrepreneurship context theory is a fruitful avenue to understand the role of rural entrepreneurship in regional development, even in remote and peripheral regions. Innovation does not need to entail high-tech international environments; it can appear as the result of efforts in low-tech industries in rural and remote environments. The authors’ findings need to be scrutinized; therefore, the authors call for more research on regional innovation systems in rural environments.

It is possible for regional authorities to orchestrate a development process through the actions of a strong regional agent but also by supporting the creation of networks of small businesses that are built on trust and common interests.

This study contributes to the literature with a new perspective to the study of entrepreneurship and of regional innovation systems. Entrepreneurship research with focus on rural contexts most often highlight limits to entrepreneurship and see entrepreneurship as “just running a business”. A perspective that starts from innovation and innovative behaviour, despite the rural context and embedded resources, helps to generate new knowledge that can enrich the understanding of entrepreneurship and also be the foundation for more precise business development policies in rural settings.

This paper examines whether technological changes that promote communications between investors and managers help bridge the gap in the cost of equity capital among firms in different regions.

We use the online interaction platforms of listed firms in China and utilize brokerage presence (BP) to capture the geographic distribution of financial factors. We explore whether online interactions would reduce the cost of equity to a greater extent for firms located in low brokerage presence regions (hereafter “low-BP firms”) than those in high brokerage presence regions (hereafter “high-BP firms”).

We find low-BP firms benefit more from an improved information environment created by online interactions. We also find that posts about low-BP firms are more value-relevant and useful in processing corporate disclosures. Further, a higher number of interactions significantly enhances more informational efficiency for low-BP firms, and the effect of reducing the gap in financing costs is more pronounced when corporate information is complex.

We conclude that online interactions alleviate geography-induced information frictions and create a relatively level playing field for firms located in all regions.

The study aims to explore the digital fashion trend within the Metaverse, characterized by non-fungible tokens (NFTs), across Twitter networks. Integrating theories of diffusion of innovation, two-step flow of communication and self-efficacy, the authors aimed to uncover the diffusion structure and the influencer's social roles undertaken by social entities in fostering communication and collaboration for the advancement of Metaverse fashion.

Social network analysis examined the critical graph metrics to profile, visualize, and cluster the unstructured network data. The authors used the NodeXL program to analyze two hashtag keyword networks, “#metaverse fashion” and “#metawear,” using Twitter API data. Cluster, semantic, and time series analyses were performed to visualize the contents and contexts of communication and collaboration in the diffusion of Metaverse fashion.

The results unraveled the “broadcast network” structure and the influencers' social roles of opinion leaders and market mavens within Twitter's “#metaverse fashion” diffusion. The roles of innovators and early adopters among influencers were comparable in collaborating within the competition venues, promoting awareness and participation in digital fashion diffusion during specific “fad” periods, particularly when digital fashion NFTs and cryptocurrencies became intertwined with the competition in the Metaverse.

The study contributed to theory building by integrating three theories, emphasizing effective communication and collaboration among influencers, organizations, and competition venues in broadcasting digital fashion within shared networks. The validation of multi-faceted Social Network Analysis was crucial for timely insights, highlighting the critical digital fashion equity in capturing consumers' attention and driving engagement and ownership of Metaverse fashion.

The purpose of this paper is to inform or alert readers to the extensive use and ready availability of genetic information that poses varying degrees of social and legal danger. The eugenics movement of the 1920s and the general acceptance of genetic essentialism provide context for considering contemporary examples of the problem.

This paper takes an argumentative approach, supporting proposals with ideas from historical and current research literature.

The limits of data protection, extensive use of direct-to-consumer genetic testing and use of genetic information in white nationalist circles portend a resurgence of eugenic beliefs from a century ago.

Research-based recommendations may help to avoid extreme consequences by encouraging people to make informed decisions about the use of genetic information.

The paper counterposes contemporary understanding of genetic testing and data accessibility with the much older ideology of eugenics, leading to concerns about how white nationalists might further their aims with 21st century technology.

The primary purpose of this exploratory paper is to propose a novel analytical framework for examining corruption from a behavioral perspective by highlighting multiple issues associated with consumerism.

This paper examines the relationship between excessive consumption activities and corrupt acts, drawing upon existing literature on corruption, consumerism and consumption, as well as multiple reports and cases of corruption and money laundering in Indonesia. With regard to corruption networks, this paper analyses the associated behavioral patterns and social dynamics by using the Fraud Triangle and the Fraud Elements Triangle frameworks to examine the phenomenon of living beyond one’s means. This paper also addresses the notion of sacredness in the context of consumer activities and how such sacredness plays a role in causing otherwise honest individuals to engage in corrupt acts.

The author established that corruption represents a complex societal issue that extends across several dimensions of society, encompassing both horizontal and vertical aspects. Consequently, addressing this problem poses significant challenges. Excessive consumption has been identified as one of the various behavioral concerns that are implicated in the widespread occurrence of corruption in many nations. Individuals who partake in excessive consumption play a role in shaping ethical norms that serve to legitimize and rationalize immoral behavior, therefore fostering a society marked by corruption. The act of engaging in excessive consumption is also associated with cases of money laundering offenses that are connected to corruption and several other illicit activities. The lifestyle of corrupt individuals is one of the primary behavioral concerns associated with corruption, as “living beyond means” is the most common behavioral red flag among occupational fraud offenders worldwide. The phenomenon of consumerism may also shape the minds of individuals as if it were an “implicit religion” due to the fact that it may generate human experiences that elicit highly positive emotions and satisfy certain sacredness-associated characteristics. The pursuit of transcendental experiences through the acquisition and consumption of sacred consumption objects may heighten the incentive to commit fraudulent acts such as corruption.

This self-funded exploratory study uses document analysis to examine the corruption phenomenon in Indonesia. Future studies will benefit from in-depth interviews with former offenders and investigators of corruption.

This exploratory study contributes to advancing corruption prevention strategies. It does this by introducing a novel analytical framework that allows for the examination of several behavioral issues associated with consumerism, which have the potential to foster the proliferation of corruption.

This exploratory study highlights the importance of comprehending the intricacies of consumerism, namely, its adverse effects on the proliferation of corruption.

Traceability of food is of paramount importance to the increasingly sustainability-conscious consumers. Several tracking and tracing systems have been developed in the AgriFood sector in order to prove to the consumers the origins and processing of food products. Critical challenges in realizing food's traceability include cooperating with multiple actors on common data sharing standards and data models.

This research applies a design science approach to showcase traceability that includes preharvest activities and conditions in a case study. The authors demonstrate how existing data sharing standards can be applied in combination with new data models suitable for capturing transparency information about plant production.

Together with existing studies on farm-to-fork transparency, our results demonstrate how to realize transparency from field to fork and enable producers to show a complete bill of sustainability.

The existing standards and data models address transparency challenges in AgriFood chains from the moment of harvest up to retail (farm-to-fork) relatively well, but not what happens before harvest. In order to address sustainability concerns, there is a need to collect data about production activities related to product quality and sustainability before harvesting and share it downstream the supply chain. The ability to gather data on sustainability practices such as reducing pesticide, herbicide, fertilizer and water use are crucial requirements for producers to market their produce as quality and sustainable products.

Cloud computing services gained huge attention in recent years and many organizations started moving their business data traditional server to the cloud storage providers. However, increased data storage introduces challenges like inefficient usage of resources in the cloud storage, in order to meet the demands of users and maintain the service level agreement with the clients, the cloud server has to allocate the physical machine to the virtual machines as requested, but the random resource allocations procedures lead to inefficient utilization of resources.

This thesis focuses on resource allocation for reasonable utilization of resources. The overall framework comprises of cloudlets, broker, cloud information system, virtual machines, virtual machine manager, and data center. Existing first fit and best fit algorithms consider the minimization of the number of bins but do not consider leftover bins.

The proposed algorithm effectively utilizes the resources compared to first, best and worst fit algorithms. The effect of this utilization efficiency can be seen in metrics where central processing unit (CPU), bandwidth (BW), random access memory (RAM) and power consumption outperformed very well than other algorithms by saving 15 kHz of CPU, 92.6kbps of BW, 6GB of RAM and saved 3kW of power compared to first and best fit algorithms.

The proposed multi-objective bin packing algorithm is better for packing VMs on physical servers in order to better utilize different parameters such as memory availability, CPU speed, power and bandwidth availability in the physical machine.

This paper aims to measure the trade price impact of a recent regulatory disclosure intervention in municipal securities secondary markets, which required broker-dealers to disclose securities trading information on a near-real-time and continuing basis.

The author analyzes trade price outcomes in the preintervention and postintervention regimes using a suite of time series estimations that give heteroskedasticity-robust standard errors (Prais–Winsten and Cochrain–Orcutt), accommodate higher-order lag structure in the error term (autoregressive integrated moving average) and account for volatility clustering in the time series (generalized autoregressive conditional heteroskedasticity).

Results show that regulatory disclosure intervention significantly improved trade price efficiency in municipal securities secondary markets as daily trade price differential and volatility both declined market-wide after the disclosure intervention.

The sample consists of trades in State of California general obligation bonds; therefore, empirical findings may not be generalizable to other states, local governments and different types of bonds.

The findings highlight voluntary information disclosure as a practical and effective mechanism in disclosure regulation of municipal securities secondary markets.

Only a small body of work exists that examines information disclosure regulation in municipal securities secondary markets; therefore, this paper expands knowledge on the topic and should provide renewed impetus for regulatory efforts aimed at improving the efficiency of municipal capital markets.

Social media networks make their services freely available to all users. Users pay for the service received with the time and attention taken by the advertisements. This chapter argues that social media platforms are a unique form of monopoly driven by “the more the merrier” effect (i.e., network effects) in users' consumption. These monopolies exercise market power, not by charging higher prices to users but by “tying” larger amounts of advertising to their content. Traditional antitrust instruments designed to address excessive pricing and reduced output by monopolies need to be reframed to tame the attention economy problems in the social media industry. This chapter discusses five antitrust instruments grouped in three categories: structural, behavioral, and market-based remedies. Market-based solutions are the least explored in the literature, despite being the most promising instruments to lower the attention costs imposed on users, while preserving the economies of scope in production and the network effects in consumption, and possibly maintaining free access to social media, as we know it today.