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This research aims to specialise in the investigation of risk management for service-oriented manufacturing supply chains via two stages, highlighting its differences from manufacturing. The research article is commenced by executing an encyclopedic review of earlier research to ascertain the distinctive traits of service-oriented manufacturing supply chains and identify prevalent risks. Secondly, an empirical study in the construction field, amongst the industry hardest struck in the mist of the COVID-19 epidemic, is conducted to thoroughly inspect the resonant effect of these risks on service-oriented manufacturing supply chain performance.

In this study, to validate the resonant effect mechanism, a thorough assessment is undertaken by juxtaposing theoretical model to a newly constructed comparative model that encompasses the single effects of risks on supply chain performance.

63% variance of service-oriented manufacturing supply chain performance was showcased by the resonant effect model, compared with 46.3% in the comparative model. Moreover, each risk exerts a more glaringly significant impact on supply chain performance, asserting the mechanism of the resonant influence. Another noteworthy result involves the demand risk possessing a low effect on supply chain performance, thus emphasising the superiority of service-oriented manufacturing supply chains.

Future research endeavours should hinge on the optimal “resonant” model explosion, thereby foreseeing and alleviating worst-case scenarios to guarantee the robustness and resilience of supply chain networks.

Indubitably, reducing the intensity of the resonant effect revolves around lowering the coefficient of “a,” thereby restricting/eliminating the link among risks. Therefore, the suggested resonant impact model might thus serve as “a road map”. In light of the aforementioned considerations, it is advisable that supply chain executives employ supply chain management tactics namely avoidance, prediction, and postponement, but only after meticulous consideration the costs and benefits of adopting such strategies.

The service-oriented manufacturing supply chain features and advantages have been analysed and explained throughout the article. The data gathered during the COVID-19 pandemic is a captivating and topical point of this paper.

This study aims to examine the role of hope and hate in political leaders’ messages in influencing liberals versus conservatives’ social-distancing behavior during the COVID-19 pandemic. Given the increasing political partisanship across the world today, using the appropriate message framing has important implications for social and public policy.

The authors use two Natural Language Processing (NLP) methods – a pretrained package (HateSonar) and a classifier built to implement our supervised neural network-based model architecture using RoBERTa – to analyze 61,466 tweets by each US state’s governor and two senators with the goal of examining the association between message factors invoking hate and hope and increased or decreased social distancing from March to May 2020. The authors examine individuals’ social-distancing behaviors (the amount of nonessential driving undertaken) using data from 3,047 US counties between March 13 and May 31, 2020, as reported by Google COVID-19 Community Mobility Reports and the New York Times repository of COVID-19 data.

The results show that for conservative state leaders, the use of hate increases nonessential driving of state residents. However, when these leaders use hope in their speech, nonessential driving of state residents decreases. For liberal state leaders, the use of hate displays a directionally different result as compared to their conservative counterparts.

Amid the emergence of new analytic techniques and novel data sources, the findings demonstrate that the use of global positioning systems data and social media analysis can provide valuable and precise insights into individual behavior. They also contribute to the literature on political ideology and emotion by demonstrating the use of specific emotion appeals in targeting specific consumer segments based on their political ideology.

The findings have significant implications for policymakers and public health officials regarding the importance of considering partisanship when developing and implementing public health policies. As partisanship continues to increase, applying the appropriate emotion appeal in messages will become increasingly crucial. The findings can help marketers and policymakers develop more effective social marketing campaigns by tailoring specific appeals given the political identity of the consumer.

Using Neural NLP methods, this study identifies the specific factors linking social media messaging from political leaders and increased compliance with health directives in a partisan population.

To this date, research on tensions has been carried out on business networks and value co-creation, with no studies exploring tensions within the marketing services context. This study aims to use the three tension categories proposed by Toth et al. (2018) and Pressey and Vanharanta (2006) to address this gap by identifying the tensions experienced in the market research agency (MRA), creative agency (CA) and client relationship, as well as the processes that increase or minimize these tensions.

A total of 25 in-depth interviews were carried out with MRA, CA and client employees. NVivo 12 was used to conduct a thematic analysis to identify the overarching processes that influenced tensions.

Six second-order codes were identified, designating processes that exacerbated or minimized each of the three tensions experienced. Two new processes were identified (“adopting governance processes” and “aspects of identity formation”) which have not been previously reported. An empirical framework was developed pinpointing processes that influenced each tension category, also highlighting complex interdependencies between behavioral, emotional and structural tensions.

This study presents the perspectives of all actors within the marketing services triad providing a more nuanced understanding of tensions at the triadic level, as previous literature predominantly focused either on dyads or on networks. Furthermore, this study highlights important interdependencies between tension categories, providing novel contributions, as well as directions for future research.

Luxury brands struggle to communicate their sustainability commitments to consumers due to the perceived incongruence between “luxury” and “sustainability”. This study aims to provide luxury brands with insights on how to engage consumers with different social value orientations (SVOs) to make sustainable luxury purchases in a compatible manner. It investigates the relationships between personal values (symbolism/universalism), SVOs (pro-self/prosocial orientation) and behavioral intentions toward sustainable luxury brands. It further explores whether these relationships may differ when consumers view themselves as individuals (salient personal identity is activated) versus group members (salient social identity is activated).

Study 1 (N = 419) used an online experiment in which participants were randomly assigned to either salient personal or social identity conditions to test the proposed model. Study 2 (N = 438) used a fictional brand to further validate the findings. Hypotheses were tested using covariance-based structural equation modeling (CB-SEM) and multi-group SEM.

Results indicate that prosocial orientation significantly increases consumers’ behavioral intentions toward sustainable luxury brands. Interestingly, pro-self-orientation can also drive intentions to support sustainable luxury brands when consumers’ personal identity is salient. Salient social identity can further strengthen the relationship between prosocial orientation and sustainable luxury behavioral intentions.

This study presents a novel, inclusive definition of sustainable luxury brands and adds theoretical rigor to the SVO framework by revealing the moderating role of salient identities, contributing to the body of knowledge in luxury brand research.

Leadership for learning emerged as an integrated leadership framework; however, attempts to establish an empirical measurement model have been limited. Critically, not much is known about how much teachers' beliefs (e.g. self-efficacy) can mediate leadership for learning impact on teacher behaviors. This study establishes a leadership for learning measurement model and examines whether teacher self-efficacy mediates the effect of leadership for learning tasks on teacher collaboration, instructional quality, intention to leave current schools and their confidence in equitable teaching practice.

Drawing on the most recent 2018 Teaching and Learning International Survey (TALIS), the study employed a structural equation modeling mediation approach.

Results suggested that teacher self-efficacy statistically significantly mediated 16 out of 20 of the relationships between leadership for learning task domains and teacher outcomes. Especially, in explaining the variance in instructional quality and teacher confidence in implementing equitable teaching practices, considerable proportions of the predictive power of leadership for learning tasks were accounted for (i.e. mediated) by teacher self-efficacy.

School-wide efforts to craft the school vision for learning must be coupled with enhancing teacher self-efficacy. Critically, leadership efforts may fall short of implementing equitable teaching practice and quality instruction without addressing teacher confidence in their ability in instruction, classroom management and student engagement.

This study is the first of its kind to evidence teacher self-efficacy mediates leadership for learning practice impact on teacher behaviors.

The empirical study of factors related to digital transformation (DT) in the banking sector is still limited, even though the importance of the topic is universally evident. To bridge that gap, this paper aims to explore the role of digital leadership (DL), innovative culture (IC) and technostress inhibitors (TI) to support engagement for improved digital innovation (DI). Based on the literature, these variables are crucial aspects of digitalisation, even though there is no agreement on their conclusiveness.

This quantitative study tested a new conceptual model using survey data from five major banks in Libya. Partial least squares structural equation modelling was used to analyse the data from the 292 usable responses.

The results showed that DL and IC positively affect DI. Techno-work engagement (TE) mediated the relationship between leadership, culture and innovation. TI played a significant moderating role in leadership, culture and engagement relationships.

The research findings highlight critical issues about how leadership style and fostering organisational support in the banking sector can enhance DT. Leaders must demonstrate a commitment to long-term resource allocation to avoid possible negative effects from digital stress while pursuing DI through work engagement.

The study suggests that fostering organisational support can enhance DT in retail banks, potentially leading to improved customer experiences and increased access to financial services. These programs will help banks contribute to societal and economic development.

This timely study examines predictor mechanisms of innovation in retail banking that resonate within the restrictions of organisational and DI frameworks and the social exchange theory. Exploring the intervening effect of TE in the leadership, culture and innovation associations is unprecedented.