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Two-sided messages in advertising, which contain both negative and positive information, can have varying effects on persuasion. Thus, it is crucial to understand the conditions under which such messages are more or less effective compared to one-sided messages that only contain positive information. This research investigates the moderating role of the visual angle (close-up vs. long shot) of an image by drawing upon construal level theory.

This research reports two experimental studies employing a 2 (message: two-sided [positive and negative information], one-sided [positive information as a control condition]) × 2 (visual angle: near [close-up], distant [long shot]) between-subjects design.

The results demonstrate that two-sided messages paired with a close-up image decrease positive electronic word of mouth (eWOM) due to increased feelings of ambivalence, while two-sided messages paired with a long-shot image increase positive eWOM due to increased perceived authenticity.

These findings provide insight into the impact of two-sided messages on advertising persuasion and provide guidance for marketers in developing effective communication strategies to leverage positive eWOM.

A key challenge for exporters and international marketing/purchasing managers is formulating strategic responses to deal with geopolitical disruptions during a trade war between superpowers. While past studies provide insightful analysis of the influence of changes in the institutional environment (regulatory pressures) on national and firm-level trade activities, they tend to ignore the association between inward (sourcing) or outward (export) international activities of firms during a trade war. In this study, we aim to explore various strategic options employed by third-party SME exporters in response to geopolitical disruptions, institutional pressures and constraints during a trade war.

We adopted a qualitative methodology and applied a hermeneutical approach in collecting, analysing and theorising interview findings. We conducted interviews with 15 owners or senior managers from 12 Australian and New Zealand exporters that exported or sourced significantly from at least one party of the trade war, the USA or China, between 2018 and 2020.

Our study developed a typology of fencing vs. balancing for explaining third-party SME exporters’ response strategies in terms of export market and international sourcing locations during a trade war. Fencing strategy centres on location choice decisions based on a fence or a secure buffer zone. Balancing strategy focuses on leveraging opportunities outside the conflict zone, i.e. third-party countries. Our study finds that exporters’ location choice decisions are influenced by a number of institutional factors during the trade war.

Firstly, our study examined only the early phase of the trade war under the “Trump” era. Future research may consider a longitudinal study design that examines exporters’ responses to global political uncertainty over a longer term. Secondly, we chose Australia and New Zealand as the focal context of this study. Future research could investigate exporters from other third-party countries that have different institutional conditions during the US-China trade war.

Firstly, an exporting firm should monitor and assess closely the wider changes in international relations between their home country’s major security partner and major trading partner, and the impact of these changes on the political risks of operating in international locations. Secondly, as the trade war intensifies, the fencing option needs to be given a greater weight than the balancing option in the strategic decision making of an exporter from a third-party country. Lastly, we encourage marketers and managers to reflect on and differentiate short-term and long-term benefits in strategic market-sourcing location decisions.

Our study makes a pioneering effort to theorise the linkages between institutional factors and the combined evaluation of export market selection and sourcing location selection choices under global political uncertainty based on the institution-based view. We present a conceptual framework highlighting the importance of institutional avoidance, embeddedness, comparative institutional advantages and multiple institutional logics for SME exporters’ international location selections during the trade war. Furthermore, we combine these institutional factors into two overarching constructs namely institutional buffer and institutional pluralism.

The COVID-19 pandemic has caused havoc on a global scale for supply chains, which put forward higher demand for organizations to reassess their global supply chain strategy and improve supply chain sustainability. The purpose of this paper is to understand how leader's paradoxical cognition affect supply chain sustainability.

This study conceptualizes a research model grounded in upper echelons theory and propose a chain-mediating model under the moderating effect of big data analytics. Using PLS-SEM method, we test the hypotheses using survey data collected from supply chain managers or leaders of the supply chain team from 193 firms.

The results indicate that supply chain ambidexterity and organizational learning play a mediating role in the relationship between leaders' paradoxical cognition on supply chain sustainability, respectively, and these two variables have a chain-mediating role in the relationship above. In addition, the big data analytics negatively moderates the relationship between leader's paradoxical cognition and organizational learning, and further moderates our chain mediating model.

This research initiatively focuses on the micro-foundations of supply chain sustainability from managerial cognition and firstly provides empirical evidence about the impact of leader's paradoxical cognition on supply chain sustainability.

Existing studies have paid less attention to the impact of knowledge accumulation on digital transformation and its boundary conditions. Hence, this study aims to investigate the effects of ambidextrous knowledge accumulation on manufacturing digital transformation under the moderation of dynamic capability.

This study divides knowledge accumulation into exploratory and exploitative knowledge accumulation and divides dynamic capability into alliance management capability and new product development capability. To clarify the relationship among ambidextrous knowledge accumulation, dynamic capability and manufacturing digital transformation, the authors collect data from 421 Chinese listed manufacturing enterprises from 2016 to 2020 and perform analysis by multiple hierarchical regression method, heterogeneity test and robustness analysis.

The empirical results show that both exploratory and exploitative knowledge accumulation can significantly promote manufacturing digital transformation. Keeping ambidextrous knowledge accumulation in parallel is more conducive than keeping single-dimensional knowledge accumulation. Besides, dynamic capability positively moderates the relationship between ambidextrous knowledge accumulation and manufacturing digital transformation. Moreover, the heterogeneity test shows that the impact of ambidextrous knowledge accumulation and dynamic capabilities on manufacturing digital transformation varies widely across different industry segments or different regions.

First, this paper shifts attention to the role of ambidextrous knowledge accumulation in manufacturing digital transformation and expands the connotation and extension of knowledge accumulation. Second, this study reveals that dynamic capability is a vital driver of digital transformation, which corroborates the previous findings of dynamic capability as an important driver and contributes to enriching the knowledge management literature. Third, this paper provides a comprehensive micro measurement of ambidextrous knowledge accumulation and digital transformation based on the development characteristics of the digital economy era, which provides a theoretical basis for subsequent research.

This study aims to explore the different effects of inter-community group networks and intra-community group networks on group innovation.

The authors used a pooled panel dataset of 12,111 self-organizing innovation groups in 463 game product creative workshop communities from Steam support to test the hypothesis. The pooled ordinary least squares (OLS) model is used for analyzing the data.

The results show that network constraint is negatively associated with the innovation performance of online groups. The average path length of the inter-community group network negatively moderates the relationship between network constraint and group innovation, while the average path length of the intra-community group network positively moderates the relationship between network constraint and group innovation. In addition, both the network density of inter-community group networks and intra-community group networks can negatively moderate the negative relationship between network constraint and group innovation.

The findings of this study suggest that network structural characteristics of inter-community networks and intra-community networks have different effects on online groups’ product innovation, and therefore, group members should consider their inter- and intra-community connections when choosing other groups to form a collaborative innovation relationship.

This study aims to examine the impact of the COVID-19 pandemic on knowledge-sharing drivers in small- and medium-sized family firms within the restaurant and fast-food industry. The pandemic has led to significant changes in business culture and consumer behaviour, accelerating digital transformation, disruptions in global supply chains and emerging new business opportunities. These changes have also influenced knowledge sharing (KS) and its underlying drivers.

To address the research objectives, a two-phase study was conducted. In the first phase, an exploratory analysis using the Delphi method was used to identify the essential drivers and factors of KS in family businesses (FBs). This phase aimed to establish a conceptual model for the study. In the second phase, confirmatory factor analysis was conducted to analyse the impact of the COVID-19 pandemic on the identified knowledge-sharing drivers. The study examined both the pre-pandemic and post-pandemic periods to capture the shifts in attitudes towards KS.

The findings indicate a significant shift in attitudes towards knowledge-sharing drivers. Before the pandemic, organisational drivers played a central role in KS. However, after the emergence of the pandemic, technological drivers became more prominent. This shift highlights the impact of the COVID-19 pandemic on KS within FB.

The research contributes to understanding knowledge-sharing in the context of FBs and sheds light on the specific effects of the COVID-19 pandemic on knowledge-sharing drivers. The insights gained from this study can inform strategies and practices aimed at enhancing KS in similar organisational settings.