Journal of High Technology Management Research最新文献

Purpose

This study investigates the affective technology acceptance model applied to the case of blockchain through Twitter text mining.

Design/methodology/approach

The analysis focuses on mapping the acceptance drivers of the blockchain technology by visualizing the users perception constructs through Blockchain hashtags. More than 5000 relevant tweets per day were collected between December 15, 2020, and January 15, 2021. The Kruskal-Wallis and the Mann-Whitney tests were applied over the frequency of the characteristics and the emotions' measurements to validate the research hypotheses.

Findings

The results prove that users show more interest in security, shareability, and decentralization characteristics. Therefore, the blockchain technology usefulness is rather perceived in the informational domain, and the blockchain ease of use is further expressed in smart contracts as a use case. Blockchain benefits are more discussed than the drawbacks among Twitter users. Besides, positive feelings with strong emotions of trust and joy dominate among users. In summary, the results show significant awareness of users towards blockchain technology.

Originality

To the best of the authors' knowledge, this paper is the first study that explores the affective technology acceptance model with user-generated content analysis.

Indian Healthcare system is a complex and distinguished structure due to variety of factors viz. population size it serves, presence of organized and unorganized services of healthcare, economic disparity and governance structure among others. Extant research emphasizes on the aspects like transparency, trust, disintermediation, non-repudiation, benchmarking of processes and practices, traceability and data integrity among others to stimulate the Indian Healthcare system for an improvised and more effective format. Blockchain Technology is recent innovation that offers many of these aforementioned aspects as a feature to the host systems. However, it is critical to understand and articulate the utility of Blockchain Technology specific to the Indian Healthcare system. Further, it is important to gauge the requirement elicitation of key stakeholders for Blockchain Technology adoption in Indian Healthcare system w.r.t any attribute prioritization/customization or design considerations (Consensus mechanism, type of blockchain, smart contracts etc.). There have been some research works on aspects of Blockchain applications in Indian Healthcare but lack a strong perspective of stakeholder requirements. We use Value-Focused Thinking framework based on discussions with the stakeholders to address the above mentioned research premise. We identify Fundamental Objectives and Strategic Objectives from the stakeholder interactions that contribute to the strategic goal. This is a niche work with a significant analytical contribution from the information systems perspective of Blockchain Technology adoption in the Indian Healthcare ecosystem given the light of premises from realms of human agents, behavioural and applications requirement from a stakeholder viewpoint.

Technology is developing rapidly. Every year, new products and services are produced that may affect the way employees work in organizations. Following and adapting to technological developments may be an individual challenge. People may experience anxiety in this process. Also, automation technologies may lead to a perception that individuals may lose their jobs soon. This may affect employees' choices in the possible human-robot collaboration process. In this study, we reached out to employees from various sectors via internet survey. The statistical analyses showed that concerns about the speed of technology affects employees' job insecurity caused by robots and the perception of job insecurity related to their work affects the level of automation they prefer in robots. New studies on this subject may contribute to the efficiency of human-robot cooperation which is expected to happen soon. Also, it may contribute to highlighting the anxiety experienced by employees during the development of technology.

Purpose

This study intends to extend the literature on IT business value by unveiling the organizational values and hindrances of blockchain adoption in the banking industry.

Design

The study incorporated a mixed-method qualitative analysis composed of semi-structured interviews (15 experts), a two-panels Delphi study (26 & 20 experts), and a systematic literature review of 35 papers about blockchain adoption. In total, 65 experts from Europe, Asia, and the Middle East working in the banking industry participated in our study.

Findings

The Delphi study ended up in a list of 25 organizational values and 20 barriers. The values were classified into four main categories: business, strategy, operation, and knowledge management, while the barriers were classified into three main categories: technological, organizational, and environmental. The study shows that the most critical organizational values of blockchain in the banking industry are related to business operations. It will increase the transparency, traceability, and trustworthiness of business processes. The least essential organizational values of blockchain are related to the business strategy domain: flexible business models, the flexibility of compliance to regulations, and certain ROI. The study shows that the most critical barriers to extracting value from blockchain in the industry are organizational and environmental, lack of understanding by top managers, compliance and regulatory requirements, and marketing noise.

Value

Theoretically, this study will extend the literature on blockchain business value, and practically it can provide insights for managers regarding mechanisms to maximize value from the blockchain. We recommended some future studies as well.

Open innovation and distributed ledger technology (DLT) are both based on the underlying principles of distribution and sharing. While open innovation is about sharing knowledge to improve innovation processes and performance, DLT is a distributed data ledger that is utilized to enhance efficiency, reduce costs, and ensure immutability, traceability, security, and transparency. In this paper, we investigate the barriers to open innovation currently faced by small and medium-sized companies (SMEs) that DLT can solve. To achieve this goal, we conducted semi-structured interviews with 11 experts in open innovation and DLTs from Spain, Germany, Australia, and India. The results of our exploratory study show that DLTs can help to solve several problems, including external barriers, such as problems with contracts, financing, lack of trust, raw materials, lack of information, domestic and international market limitations, IP rights, and governmental regulations as well as bureaucracy. Internal challenges include insufficient funding, organizational systems that are out of date, and lack of trust. When it comes to difficulties associated with the management of open innovation, external barriers are frequently caused by customers' demands, while internal barriers are frequently caused by organizational culture or human nature, which cannot be improved by DLTs. Finally, SMEs might face new obstacles when integrating DLTs, such as integration problems, complex transition phases, and high setup costs as well as problems with attracting and retaining qualified employees.

This research examines for the first time the relationship between Big data and Smart data among French automotive distributors. Many low-tech firms engage in these data policies to improve their decisions and performance through the predictive capacities of their data. A discussion emerges in the literature according to which an effective policy lies in the conversion of a mass of raw data into so-called intelligent data. In order to understand better this digital transition, we question the transformation of data policies practiced in low-tech firms through the founding model of 3Vs (Volume, Variety and Velocity of data). First of all, this empirical study of 112 French automotive distributors develops the existing literature by proposing an original and detailed typology of the data policies practiced (Low data, Big data and Smart data). Secondly, after specifying the elements of the differences between the quantitative nature of Big data and the qualitative nature of Smart data, our results reveal and analyse for the first time the existence of their synergistic relationship. Companies transform their Big data approach into Smart data when they move from massive exploitation to intelligent exploitation of their data. The phenomenon is part of a high-end loop data exploitation. Initially, the exploitation of intelligent data can only be done by extracting a sample from a large raw data pool previously made by a Big data policy. Secondly, the organization's raw data pool is in turn enriched by the repayment of contributions made by the Smart data approach. Thus, this study develops three important ways. First off, we identify, detail and compare the current data policies of a traditional industry. Secondly, we reveal and explain the evolution of digital practices within organizations that now combine both quantitative and qualitative data exploitation. Finally, our results guide decision-makers towards the synergistic and the legitimate association of different forms of data management for better performance.

The concept of smart tourism remains fuzzy when it comes to practice because of the lack of clarity on the roles and responsibilities of stakeholders in addition to complex institutional ecosystem that exist within the tourism industry. Further, trust and safety of the data generated due to the advancement of smart tourism in varied institutional arrangements pose huge challenges. Extant literature proposes that the application of decentralized ledger promises possible solutions to most of these problems due to the inherent features of the Blockchain technology. This suggestion raises two practical questions. First, does the sophisticated additional layer adds complexity to its practical application? Second, will the suggested solutions really lead to a win-win for all the stakeholders involved? In this study, we use Ostrom's action arena to examine the exchanges (information, contractual and monetary) between various stakeholders in a BCT enabled smart tourism of a Blockchain enabled tourism industry to answer these two questions.

Purpose

Exploring factors that can influence employee's entrepreneurial intentions is critical to entrepreneurship and entrepreneurial practice. This study is going to examine the effect of narcissism on entrepreneurial intentions. Moreover, the mediating role of entrepreneurial self-efficacy in narcissism-entrepreneurial intentions link is also tested. Lastly, how environmental complexity moderates these relationships is explored.

Design/methodology/approach

Data were collected from 362 employees working in technology incubators and science parks of Saudi Arabia. These technology incubators and science parks were established by the Saudi government as a part of entrepreneurship ecosystem evolution strategy to encourage and support entrepreneurial innovations.

Findings

The results show that narcissistic employees display greater levels of entrepreneurial intentions, and entrepreneurial self-efficacy mediates the effect of narcissism on entrepreneurial intentions; and environmental complexity moderates the narcissism-entrepreneurial intentions link.

Originality

The effect of narcissism on entrepreneurial intentions has not been examined before. This study extends knowledge on entrepreneurial innovations by linking narcissism with entrepreneurial intentions through mediation of entrepreneurial self-efficacy and moderation of environmental complexity.

Tax incentives and direct funding are two different public support instruments used to facilitate the formation and growth of firms. Limited empirical evidence has compared the effectiveness of two different policies and their interactions for firms. In this paper, we investigate the main and interaction effects of these interventions on high-tech firms. Since large and small firms innovate in different ways, we compare the use of both incentives by Iranian high-tech SMEs and large firms through a factorial design technique. This paper presents significant differences both across instruments and across firm size. Results show that for SMEs, tax exemption has a significant effect on R&D investment, and funding has a significant effect on R&D investment, R&D employees, and new products. However, there aren't any interaction effects between instruments. For large firms, funding is an effective instrument for R&D investment. Also, there is an interaction effect between tax incentives and direct funding on new products. These findings indicate that funding is a more effective instrument than tax exemption, especially for SMEs, but suggest some changes in supporting policies of high-tech firms in Iran.

Studies on the adoption of Blockchain technology (BT) in supply chains have recently gained considerable importance because BT can enable secure, scalable, reliable, and traceable information sharing among partners. In this paper, the value of the adoption of BT is analysed in a single supplier and multi-retailer arrangement wherein the demand at retailers could be correlated. The newsvendor model and game theory are used to analyse the expected profit generated by the supplier and retailers from the adoption of BT. The demand pattern (stationary or nonstationary) and structure (number of retailers participating in a private/permissioned BT) affect BT adoption in a single supplier and multi-retailer supply chain coordination. The retailer's incentive increases when more number of retailers with independent demand participates in the BT framework.