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This paper aims to explore various factors associated with radio frequency identification (RFID) adoption with quantitative meta-analysis. More specifically, this paper attempts to measure key variables of RFID adoption derived from Rogers’ innovation theory and further examines how state intervention influences the process of RFID adoption. First, this paper compares, relying on a meta-analysis, various mean effect sizes among technological, organizational and environmental factors (i.e. government-driven policies) that Rogers suggested in his innovation model.

In mean effect size analysis, this paper finds that the technological factor is the most powerful factor that affects the RFID adoption. The technological factor is statistically significant across all regions, including North America, Europe and Asia. The organizational factor is significant only in developing countries like Southeast Asian countries and East Asian countries. Environmental factors like government intervention for facilitating RFID adoption are strong enough only in Southeast Asia and Europe.

This paper finds that government’s supportive policy is more effective in Europe but not in America, while external pressure is still more effective in Southeast Asia. These results implicate that developmentalism or government-driven policy can be effective not only in developing countries but also in the case of developed countries. In addition, this paper conducts a seemingly unrelated regression (SUR) analysis based on Fisher’s standardized score.

In SUR analysis, this paper finds that the correlations between RFID adoption intention and three innovation factors vary across industrial areas. More specifically, the manufacturing area shows negative moderating effect on all three equations where correlations between Rogers’ innovation factors and RFID adoption intention are meta-dependent variables. Also, RFID adoption is accelerated when the size of the firm is large or the location of the firm is in Southeast Asia. This result implicates that the aspect of technology adoption can be changed by region and type of industry.

This study aims to investigate the motivations for the adoption of Industry 4.0 technologies among manufacturing firms in developing economies. Specifically, the effects of relative advantage of the technologies, competitive pressure, and government support on the adoption are explored. Moreover, the mediating role of top management support between environmental factors (government support and competitive pressure) and the adoption of Industry 4.0 technologies is examined.

A research model is developed based on the technology-organization-environment (TOE) framework strengthened by institutional theory. Structural equation modeling (SEM) approach is employed to evaluate the model using data obtained from 215 manufacturing firms through a cross-industry survey. Additionally, a post-hoc analysis is conducted using cluster analysis and ANOVA.

The results show that competitive pressure and government support significantly promote top management support, which in turn contributes to the adoption of Industry 4.0 technologies. Relative advantage of the technologies is not significantly related to the adoption.

This study does not explore the relationship between technology type and the specific needs of manufacturing firms. Future researchers can conduct a more comprehensive analysis by examining how different technology types align with the unique needs of individual companies.

The findings of this study have implications for both policymakers and managers. Policymakers can leverage these insights to understand the underlying motivations behind manufacturing firms' adoption of Industry 4.0 technologies and develop promoting policies. In turn, managers should keep an eye on government policies and utilize government support to facilitate technology adoption.

This study uncovers the underlying motivations—government support and competitive pressure—for the adoption of Industry 4.0 technologies among manufacturing firms in developing economies. Meanwhile, it complements previous research by showing the mediating role of top management support between environmental factors (government support and competitive pressure) and the adoption of Industry 4.0 technologies.

The purpose of this paper is to investigate the relationship between the characteristics of the incubation industry, government funding, and the intensity of funding for different services. Because the incubation industry has particular characteristics, government funding varies for different services, and its intensity varies with service.

Government funding is classified as incubation subsidy and incubation incentive. Besides, incubation services include property management, business mentoring as well as investment and financing. Based on this, this study examines the influence mechanism of different subsidy and incentive on incubation services by using the generalized propensity score matching method.

The empirical results show that subsidy and incentive have an inverse-U shape effect on property management service, but a linear effect on business guidance service. Furthermore, subsidy does not affect investment and financing service, but incentive that can have a significant impact.

The theme of government funding and incubator services plays an important role in helping entrepreneurs expand their businesses. Incubation subsidy and incentive can provide important support to help enterprises obtain more preferential loans, technical services and technical support in the incubator. Applying it to incubator services can provide better technology and entrepreneurship guidance. These services can help new entrepreneurs understand products and markets, and how to develop more successfully in the early stage. In short, incubators supported by government funds can provide important support to entrepreneurs to help them successfully realize their business plans.

Hazard risk communication has arguably been a challenge, especially in communities which are susceptible to multiple hazards. Orewa was specially chosen for this research in order to provide a complete assessment of the effectiveness of communicating New Zealand's early warning strategy in a multi-hazard area. Two categories of surveys were undertaken; experts and academics in emergency management and disaster risk resilience and the Orewa community. A semi-qualitative indicator-based analysis was conducted with the normalization of index values which resulted in four (4) categories; risk perception, risk awareness, risk governance and uncertainty, trust and credibility. The resulting vulnerability index indicated that risk perception and uncertainty, trust and credibility ranked the highest, followed by risk awareness and risk governance. Risk perception had stark differences between what the community perceives as being most at risk from to what the experts deem to be the highest risk for Orewa. This has implications for policy directives as well as funding for risk reduction. Uncertainty, trust and credibility was another area which indicated conflicting sentiments between the community and experts. The community generally trusts decision-makers but the experts think they don't. This shows that the community is aware of their risks, but may not necessarily believe that the experts are providing enough efforts in what is of importance to them. Risk governance is not a vulnerable area to the experts as they have been actively engaging in hazards that they deem Orewa was most at risk from. Any breakdown in communication can have detrimental effects if multiple hazards were to occur at once in the case of Orewa.

Relational contracting is increasingly being applied to complex and uncertain construction projects. However, it has proved hard to achieve stable performance and industry-level learning in this field. This paper employs an institutional perspective to analyze how legitimacy for relational contracting has been produced and challenged in Denmark, Finland, Norway and Sweden, including implications for dissemination and learning.

A collaborative case study design is used, where longitudinal accounts of the developments in relational contracting over more than 25 years in four Nordic countries were developed by scholars based in each country. The descriptions are underpinned by literature sources from research, practice and policy.

The countries share similar problem perceptions that have triggered the de-institutionalization of traditional contracting practices. Models and policies developed elsewhere are important sources of knowledge and legitimacy. Most countries have seen pendulum movements, where dissemination of relational contracting is followed by backlashes when projects fail to meet projected outcomes. Before long, however, relational contracting tends to re-emerge under new labels and in slightly new forms. Such a proliferation of concepts presents further obstacles to learning. Successful institutionalization is found to rely on realistic goals in combination with broad competence development at the organizational and industry levels.

In seeking inspiration from other countries, policymakers should go beyond contract models to also consider strategies to manage industry-level learning.

The paper provides a unique longitudinal cross-country perspective on the field of relational contracting. As such, it contributes to the small stream of literature on long-term institutional change in the construction sector.

The purpose of this study is to analyze the environmental efficiency level and trend of the transportation sector in the upper–mid–downstream of the Yangtze River Economic Belt and the JingJinJi region in China and assess the effectiveness of policies for protecting the low-carbon environment.

This study uses the meta-frontier slack-based measure (SBM) approach to evaluate environmental efficiency, which targets and classifies specific regions into regional groups. First, this study employs the SBM with the undesirable outputs to construct the environmental efficiency measurement models of the four regions under the meta-frontier and group frontiers, respectively. Then, this study uses the technology gap ratio to evaluate the gap between the group frontier and the meta-frontier.

The analysis reveals several key findings: (1) the JingJinJi region and the downstream of the YEB had achieved the overall optimal production technology in transportation than the other two regions; (2) significant technology gaps in environmental efficiency were observed among these four regions in China; and (3) the downstream region of the YEB exhibited the lowest levels of energy consumption and excessive CO₂ emissions.

To evaluate the differences in environmental efficiency resulting from regions and technological gaps in transportation, this study employs the meta-frontier model, which overcomes the limitation of traditional environmental efficiency methods. Furthermore, in the practical, the study provides the advantage of observing the disparities in transportation efficiency performed by the Yangtze River Economic Belt and the Beijing–Tianjin–Hebei regions.

The current study is designed to investigate the factors that foster the framing of destination competitiveness and establish the factors that drive the contribution of tourism innovations to economic growth in smart tourism destinations.

A four-year panel data were extracted from the World Economic Forum's travel and tourism competitiveness index and data were analysed using Poisson Pseudo Maximum Likelihood regression model.

The findings demonstrate that both the enabling environment and airport infrastructure significantly affect tourism's impact on the economy of the selected smart European tourism destinations. Conversely, human resources and general infrastructure display a negative correlation with tourism's contribution to the economy. However, no data in the sample support the idea that tourism policies, government prioritization or readiness of tourism information and communication technologies impact tourism's contribution to the economy. Additionally, the marginal effects indicate that improving the enabling environment and airport infrastructure can generate additional benefits for the economy through tourism.

The uniqueness of this study is the integration of smart tourism destinations with the measure of destination competitiveness to provide an empirical bridge that links tourism competitiveness to economic growth.

Reactance theory is applied to investigate consumer responses to “buy local” campaigns initiated by government to counteract the effects of an economic crisis, using the COVID-19 pandemic as an illustrative context.

A conceptual model is developed, aimed at revealing the extent to which “buy local” campaigns – explicitly justified by the need to fight an economic crisis – are likely to lead to (a) compliance (i.e. support for local products/retailers) or (b) freedom restoration (i.e. support for foreign products/retailers). The model is subsequently tested on samples of German (N = 265) and Italian (N = 268) consumers.

“Buy local” campaigns are likely to generate reactance amongst consumers and such reactance can lead to both non-compliance and, albeit less so, freedom restoration outcomes. At the same time, consumer ethnocentrism acts as a countervailing influence by attenuating the effects of generated reactance and its undesirable outcomes.

Psychological reactance theory offers a novel perspective for conceptually approaching the likely responses of consumers towards “buy local” campaigns and the empirical findings support the use of the theory in this context.

Policymakers seeking to encourage consumers to support the local economy during times of an economic crisis need to be aware that “buy local” campaigns may, against their intended communication goals, result in non-compliance as well as consumer responses in the opposite direction. Thus, the reactance-generating potential of such campaigns needs to be explicitly considered at the planning/implementation stage.

The findings confirm the relevance of reactance theory as a conceptual lens for studying the effects of “buy local” campaigns and have important implications for domestic/foreign firms as well as for policy makers seeking to encourage consumers to support the local economy during times of an economic crisis.

As cryptocurrencies continue to gain viability as an asset class, institutional investors and publicly traded firms have started taking investment positions in digital currencies. What firms may not be considering, however, is the effect these assets may have on their risk profiles. This study aims to (1) measure the effect of cryptocurrencies on the risk and return characteristics of publicly traded companies; (2) decipher the motives behind holding cryptocurrencies as an asset class; and (3) determine whether one reason for holding is more effective than another. To conduct this research, the four largest publicly traded holders of cryptocurrency as well as four of the most prominent cryptocurrencies are explored.

The cross-sectional analysis approach has been used to analyze the daily returns, volatility, betas and Sharpe Ratios of firms during periods without cryptocurrency strategies and during periods with cryptocurrency strategies.

The impact of the cryptocurrency asset class on common stock performance and corporate disclosures are documented. The importance of risk disclosures on cryptocurrency holdings is emphasized: Firms must better inform their stakeholders through comprehensive disclosures in financial statements. Firms utilize cryptocurrencies for various reasons such as treasury management tools or as direct sources of income. Consequently, the impact on returns and risks varies substantially.

To the best of the authors’ knowledge, this is one of the first studies on cryptocurrency investments in the treasury departments of publicly traded companies. The study contributes to the literature by extracting relevant information regarding company risk reporting and cryptocurrency risk at firms. The conclusions also promote firm transparency with detailed reporting of cryptocurrency holding risks.

The ongoing COVID-19 pandemic highlights the importance of destination marketing and media profiling to re-engage international tourists. However, potential crisis-induced nation brand (NB) deficits must be addressed to re-ignite tourism demand. The study examines the possible intervening effect of the contemporary NB in the international destination marketing and media-travel motives nexus.

A deductive quantitative study was undertaken with an online Amazon Mechanical Turk sample of n = 454 respondents. Hypotheses were tested using PROCESS Macro, Model 4.

The results show that the NB [people and negative events] had a practically significant partial mediating effect in the destination marketing – nature-cultural oriented travel motivation nexus.

New insights are provided via a practical model which facilitates the measurement of potential nuances in the influence of destination marketing and media profiling on leisure tourists' travel motives amid crises. The intervening effect implies that a better understanding of the NB as an indirect antecedent to travel motivation may result in more effective crisis communications and tourism recovery-oriented marketing.

The study is amongst the first to extend marketing and behavioural theory to explore the interplay between the marketing and media profile, a nation's brand and tourists' travel behaviour amid a crisis. The study addresses a discernible dearth of knowledge related to the influence of the NB on tourist behaviour from an emerging market perspective.