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This paper aims to deepen the understanding of the relationship between global economic uncertainty and price volatility, specifically focusing on commodity, industrial materials and energy price indices as proxies for global inflation, analyzing data from 1997 to 2020.

The dynamic conditional correlation generalized autoregressive conditional heteroscedasticity model is used to study the dynamic relationship between variables over a while.

The results demonstrated a positive relationship between commodity prices and the global economic policy uncertainty (GEPU). Except for 1999–2000 and 2006–2008, the results of the energy price index model were very similar to those of the commodity price index. A predominant positive relationship is observed focusing on the connection between GEPU and the industrial material price index. The results of the pairwise Granger causality reveal a unidirectional relationship between the GEPU – the Global Commodity Price Index – and the GEPU – the Global Industrial Material Price Index. However, there is bidirectional causality between the GEPU – the Global Energy Price Index. In sum, changes in price indices can be driven by GEPU as a political factor indicating unfavorable economic conditions.

This paper provides a deeper understanding of the role of global uncertainty in the global inflation process. It fills the gap in the literature by empirically investigating the dynamic movements of global uncertainty and the three most important groups of prices.

The rising complexity of business changes has increasingly highlighted the requirements to provide a comprehensive and empirical framework for the supply chain agility (SCA). A review of extant studies shows that the results are complicated and ambiguous. Moreover, this study is a meta-analytical review of previous empirical studies to identify SCA antecedents and effects of SCA on firm performance.

According to the protocol, 64 studies were chosen as the sample to survey the relationships between five clusters of SC allopoietic properties (SCAPs) (SC connectivity, symbiotic relationship (SR), cognitive openness (CO), homeostasis and collaboration) and SCA, as well as its effects on firm performance.

Among antecedents, horizontal collaboration’s effect on SCA is the strongest, and the relationship between SR-SCA and CO-SCA is less than moderate. SCA affects firm performance and its dimensions, with a stronger effect on financial performance (FP). Furthermore, the SCA study in the framework of allopoietic systems is a good starting point for future research.

Managers are advised to constantly review repetitive interactions between the company and its environment and to learn about interactions between SC and the environment. Learning from these interactions and disseminating their explicit knowledge among company members lead to a quick response to the environmental instability.

As the first meta-analysis on SCA antecedents and its effects on firm performance, this study contributes to the SCA literature and provides research directions for the future.

How to promote innovation remains a challenge. In practice, some enterprises try to initiate an organizational crisis intentionally to spur innovation. This study approaches this practice and aims to explore the role of intentional organizational crisis in innovation.

This study conducted an empirical study. Data was collected from 297 companies in China by a questionnaire survey.

Results show the role of intentional organizational crisis in innovation. There is a U-shaped relationship between intentional organizational crisis and product innovation capability. Past performance and resources allocation capability moderate this relationship by weakening the impact of intentional organizational crisis on product innovation capability.

This study highlights the light and dark sides of intentional organizational crisis and explores its impact on innovation capability, providing some implications for practitioners to use crises as shocks to spur innovation and enriching the research of organizational crisis and innovation capability.

Smartphone apps collect users' personal information, which triggers privacy concerns for app users. Consequently, app users restrict apps from accessing their personal information. This may impact the effectiveness of in-app advertising. However, research has not yet demonstrated what factors impact app users' decisions to use apps with restricted permissions. This study is aimed to bridge this gap.

Using a quantitative research method, the authors collected the data from 384 app users via a structured questionnaire. The data were analysed using AMOS and fuzzy-set qualitative comparative analysis (fsQCA).

The findings suggest privacy concerns and risks have a significant positive effect on app usage with restricted permissions, whilst reputation, trust and perceived benefits have significant negative impact on it. Some app-related factors, such as the number of apps installed and type of apps, also impact app usage with restricted permissions.

Based on the findings, the authors provided several implications for app stores, app developers and app marketers.

This study examines the factors that influence smartphone users' decisions to use apps with restricted permission requests. By doing this, the authors' study contributes to the consumer behaviour literature in the context of smartphone app usage. Also, by explaining the underlying mechanisms through which the principles of communication privacy management theory operate in smartphone app context, the authors' research contributes to the communication privacy management theory.

Globalization and increased outsourcing have contributed to increased supply chain complexity, exposing firms to greater vulnerability in the areas of product safety and supply chain security. Meanwhile, stakeholders pressure firms to ensure that their products are safe, and their supply chains are secure. Drawing from stakeholder theory, this paper aims to explore how the supply chain characteristics of distance and power affect the adoption of consumer protection (CP) practices, which ensure product safety and supply chain security.

Using primary survey data from a sample of Canadian manufacturing firms, this research examines the relationships among supply chain characteristics, adoption of CP practices and firm performance.

Analysis supported the use of two practices related to product safety (consumer education and product design) and three practices for supply chain security (packaging, tracking and authenticity). Greater cultural distance between the focal firm and its suppliers was positively associated with investments in safer design practices, while increased geographical distance between the focal firm and the customer was significantly related to increased consumer education. Moreover, as power of a focal firm relative to its suppliers increased, so too did investments in supply chain security. Finally, CP practices were related to improved operational performance along multiple dimensions.

This research focuses on the critical role of two key stakeholder groups in improving product safety and supply chain security: suppliers and customers. The authors add to the theoretical discussion of product safety and supply chain security by identifying critical differences between suppliers and customers for the focal firm. Second, the research informs the managerial community of the potential benefits of investments in CP practices.

This study aims to develop an interface management risk interaction modeling and analysis methodology applicable to complex systems in high-speed rail construction projects, reveal the interaction mechanism of interface management risk and provide theoretical support for project managers to develop appropriate interface management risk response strategies.

This paper introduces the association rule mining technique to improve the complex network modeling method. Taking China as an example, based on the stakeholder perspective, the risk factors and significant accident types of interface management of high-speed rail construction projects are systematically identified, and a database is established. Then, the Apriori algorithm is used to mine and analyze the strong association rules among the factors in the database, construct the complex network, and analyze its topological characteristics to reveal the interaction mechanism of the interface management risk of high-speed rail construction projects.

The results show that the network is both scale-free and small-world, implying that construction accidents are not random events but rather the result of strong interactions between numerous interface management risks. Contractors, technical interfaces, mechanical equipment, and environmental factors are the primary direct causal factors of accidents, while owners and designers are essential indirect causal factors. The global importance of stakeholders such as owners, designers, and supervisors rises significantly after considering the indirect correlations between factors. This theoretically explains the need to consider the interactions between interface management risks.

The interaction mechanism between interface management risks is unclear, which is an essential factor influencing the decision of risk response measures. This study proposes a new methodology for analyzing interface management risk response strategies that incorporate quantitative analysis methods and considers the interaction of interface management risks.

This paper aims to address three research questions (1) Who is the main stakeholder that shapes Airbnb experience, (2) Does Airbnb offers an authentic travel experience? and (3) What should be the future research trends in Airbnb?

This paper uses the systematic literature review (SLR) with a well-defined protocol, research strategy and methods to answer the research questions.

The review revealed that while Airbnb plays a significant role as the platform provider, the stakeholders influencing the experiences are multifaceted. Hosts, guests, local communities and even regulatory bodies all contribute to shaping the overall Airbnb Experience ecosystem. Hosts, in particular, have a crucial role in curating and delivering unique experiences, which significantly impacts the quality and authenticity of the offerings. On the question of whether Airbnb offers an authentic travel experience, the review uncovered mixed findings. For examples, some studies emphasized the potential for Airbnb to provide authentic and local experiences, allowing travelers to engage with the community and cultural aspects of a destination. However, other studies raised concerns about the commodification and standardization of experiences, leading to a potential loss of authenticity.

This paper is different from previous SLR where previous research systematically reviewed; motivations to use and choose Airbnb, institutionalization of Airbnb, stakeholders of Airbnb. This paper addresses authentic experience as a factor that influences activity participation.

This study aims to contribute to the field of computer systems for sustainability research. It proposes a framework for sustainability awareness using online social networks (OSNs) by analyzing major research streams of the current state of knowledge and different bibliometric variables, and identifies a future research agenda in the field.

The preferred reporting items for systematic review and meta-analysis (PRISMA) methodology, content analysis and bibliometric tools were employed to identify, select, collect, synthesize, analyze and evaluate all research published on sustainability awareness using OSNs to provide complete insight into this research area.

This study proposed a framework comprising four categories for sustainability awareness using OSNs. These four categories are: the key factors to success, analysis of existing tools, proposal of new methods, approaches and theoretical frameworks, and case examples. In addition, this study synthesized the future research challenges for each category of the proposed framework.

Fostering sustainability awareness and sustainable behavior using OSNs is a growing area of research that seeks cultural change in society to achieve sustainable development. Through OSNs, people can discover and become aware of the consequences of unsustainable practices and habits in society, and learn how to develop sustainable behavior.

The peer review history for this article is available at https://publons.com/publon/10.1108/OIR

The firms’ adoption and improvement of big data analytics capabilities to improve economic and environmental performance have recently increased. This makes it important to discover the underlying mechanism influencing the association between big data analytics (BDA) and economic and environmental performance, which is missing in the existing literature. The present study discovers the indirect effect of green innovation (GI) and the moderating role of corporate green image (CgI) on the impact of BDA capabilities, including big data management capability (MC) and big data talent capability (TC), on economic and environmental performance.

A time-lagged design was employed to collect data from 417 manufacturing firms, and study hypotheses were evaluated using Mplus.

The empirical outcomes indicate that both BDA capabilities of firms significantly influence green innovation (GI), which significantly mediates the relationship between BDA and economic and environmental performance. Our findings also revealed that CgI strengthened the effect of GI on economic and environmental performance. The empirical evidence provides important theoretical and practical repercussions for manufacturing SMEs and policymakers.

This study contributes to the literature on BDA by empirically exploring the effects of MC and TC on improving the EcP and EnP of manufacturing firms. It does so through the indirect impact of GIs and the moderating effect of CgI, thereby extending the Dynamic capabilities view (DCV) paradigm.

With the emergence of big data analytics and the importance of analytics-driven decisions, the travel industry is swiftly jumping on and adopting the bandwagon. However, research in this domain is limited. Accordingly, the present research seeks to understand how big data analytics capabilities (BDAC) add value to tourism supply chains (TSCs) and can dynamic capabilities (DC) improve the triple bottom line.

Data from 218 valid responses were collected from different Indian tourism industry units. Confirmatory factor analysis (CFA) was applied to confirm the constructs, followed by partial least squares structural equation modelling (PLS-SEM) to check the mediating effect of DC on TSCs performance.

The findings show that BDAC significantly influence the performance of TSCs and that DC plays a critical role in strengthening the impact of BDAC on TSCs' economic performance. These results corroborate that DC plays a key moderating role.

This study contributes significantly to the tourism sector in India, where tourism is a key contributor to the country's gross domestic product. Theoretically, this study contributes to the resource-based view (RBV) and practically encourages professionals in the tourism sector to promote the use of BDAC to enhance the performance of TSCs.

The originality of the study is that it has tried to comprehend the moderating role of dynamic capabilities which impact BDAC to improve TSC performance.