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This study is conducted with an aim to develop and validate self-talk scale for service sector employees designed to measure dimensions that are relevant for their conduct in job.

A three-phase study, which is conducted firstly, with a sample of 250 and then with another sample of 671 employees of service sector. Both factor exploration and confirmation are applied for testing the psychometric properties.

A well-developed and validated instrument comprising of 17 statements with four dimensions of self-talk, which are self-compassionate, rational, task oriented and self-regulation in social settings relevant to regulate ones job behaviour.

The instrument so developed becomes the first of its kind to be validated on organisational employees. The instrument provides an important means to estimate the cognitive process of self-talk, especially for employees working in fields that requires them to deal with people. Moreover, enabling individuals to understand the subtle nuances that take place in the mind while regulating ones behaviour. Thus, proving to be a promising instrument, as this can serve as a base for identifying the need for industrial training programmes or interventions.

The purpose of this study is to propose an alternative efficient 3D emotion recognition model for variable-length electroencephalogram (EEG) data.

Classical AMIGOS data set which comprises of multimodal records of varying lengths on mood, personality and other physiological aspects on emotional response is used for empirical assessment of the proposed overlapping sliding window (OSW) modelling framework. Two features are extracted using Fourier and Wavelet transforms: normalised band power (NBP) and normalised wavelet energy (NWE), respectively. The arousal, valence and dominance (AVD) emotions are predicted using one-dimension (1D) and two-dimensional (2D) convolution neural network (CNN) for both single and combined features.

The two-dimensional convolution neural network (2D CNN) outcomes on EEG signals of AMIGOS data set are observed to yield the highest accuracy, that is 96.63%, 95.87% and 96.30% for AVD, respectively, which is evidenced to be at least 6% higher as compared to the other available competitive approaches.

The present work is focussed on the less explored, complex AMIGOS (2018) data set which is imbalanced and of variable length. EEG emotion recognition-based work is widely available on simpler data sets. The following are the challenges of the AMIGOS data set addressed in the present work: handling of tensor form data; proposing an efficient method for generating sufficient equal-length samples corresponding to imbalanced and variable-length data.; selecting a suitable machine learning/deep learning model; improving the accuracy of the applied model.

Natural environments and imagery are known to have a myriad of effects on people’s physical and psychological states. However, little is known about how exposure to nature-related imagery can influence consumers’ motivational states. This research investigates the effect of exposure to nature on consumers’ regulatory focus. More specifically, this paper proposes that consumers exposed to nature will exhibit stronger promotion-oriented focus and weaker prevention-oriented focus, and as such, these consumers will prefer promotion-framed marketing messages over prevention-framed ones. This paper aims to explore a mediating mechanism and a boundary condition for this effect.

A series of six experiments, including an Implicit Association Test, examined the effect of exposure to images of natural objects and scenes (in contrast with non-nature imagery) on consumers’ regulatory focus and whether they experienced regulatory fit when encountering promotion-framed (vs prevention-framed) advertising messages.

The results revealed that consumers exhibited lower prevention-focused and higher promotion-focused motivational orientation after exposure to nature. Furthermore, exposure to nature led consumers to experience more regulatory fit with promotion-oriented marketing messages than prevention-oriented ones. This study found that natural environments offer urban consumers a reprieve from their day-to-day life, which mediates the effect of exposure to nature on regulatory focus. This study investigated the boundary condition of engaging in maintenance of nature (e.g. mow the grass) in which the effects of nature on regulatory focus were attenuated.

This study used text and pictures related to nature as a way to expose the online participants to nature. Future research may use field studies with participants in real natural settings, with expectation of stronger effects. Second, this study examined mostly urban American participants. There may be cultural differences or living situations (e.g. living “off the grid” and in the “wild”) that influence people’s relationship with nature. Future research may examine how these differences can affect the influence of exposure to nature on motivational orientation.

The findings have direct implications for marketing managers and other related stakeholders. Exposing urban consumers to nature – even images of nature – they become more receptive to promotion-framed advertisements and marketing communications (vs prevention-framed messaging).

Little is currently known about how exposure to nature can influence psychological processes such as motivational orientation. This research contributes to the understanding of consumers’ responses to nature-related imagery in advertising and the effect that nature imagery has on consumers’ motivational orientation. This research also contributes to the body of work on regulatory focus by identifying a novel context in which consumers’ motivational orientation can be influenced.

As innovations introduce novel benefits to customers, they would need to be positioned in a way that sets them apart in the market. The purpose of this paper is to propose a novel approach for the positioning of innovations with the use of the customer imagination and, specifically, mental movies.

Using the schema approach as this study’s theoretical framework, the author proposes that innovations could be positioned using moving pictures (i.e. mental movies) instead of mental pictures (the approach traditionally taken).

A new conceptual framework for the positioning of innovations using mental movies is presented. In the framework, this study outlines how innovations can be positioned with the use of mental movies, and why such an approach would be beneficial. The framework outlines mixed reality, i.e. augmented reality, augmented virtuality and virtuality, as well as the metaverse and gaming as avenues for positioning innovations using mental movies. On the benefit side, the framework identifies successful market introductions, engagement and stickiness, memorability and positive emotions, uniqueness and differentiation and market share as the concrete benefits that can be achieved with this type of positioning.

The framework provides a novel approach for the positioning of innovations. It departs from existing literature by proposing that innovations can be positioned using mental movies. The framework also identifies why this approach would be beneficial for marketers and managers and provides concrete guidelines for how such a positioning can be achieved in the market.

The construction industry is an industry which has gained notoriety when it comes to both physical and mental health problems. Compared to other industries, the construction sector has a higher prevalence of many stressors and mental health concerns. This calls for mechanisms to cope with these concerns. One coping mechanism propounded to help cope and adapt in the face of pressures and challenges is “Mental Toughness (MT)”. While mental toughness has been widely studied in various fields, there is a paucity of comprehensive research examining its significance among construction professionals. Thus, the motivation of this study is to establish the mental toughness characteristics among construction professionals in Ghana.

The construction industry is an industry which has gained notoriety when it comes to both physical and mental health problems. Compared to other industries, the construction sector has a higher prevalence of mental health concerns. One coping mechanism propounded to help cope and adapt in the face of pressures and challenges is “Mental Toughness (MT)”. While mental toughness has been widely studied in various fields, there is a paucity of comprehensive research examining its significance among construction professionals. Thus, the motivation of this study is to establish the mental toughness characteristics among construction professionals.

the study's findings revealed 13-factor model characteristics of mental toughness with 43 variables for mentally tough performers in the construction environment. These 13-factor models include Pressure Management (PM), Motivation (M), Emotional Intelligence (EI), Interpersonal self-belief (SB), Tough Attitude (TA), Job-related self-belief (SBB), Ethical Values (EV), Commitment (C), Focus (F), Optimism (OP), Expertise and Competence (EC), Imagery Control (IC) and Resilient (R).

The outcome of this study has significant practical implications for various stakeholders. For construction professionals the identified factors provide valuable insights into the psychological attributes and behaviours that contribute to mental toughness among construction professionals. Understanding these characteristics can empower professionals to develop strategies for coping with stress, maintaining focus, and fostering resilience in challenging construction environments to achieve optimum performance levels consistently.

The originality of this study's findings stems from the fact that it is among the first to provide greater insight into mental toughness characteristics considered by professionals (quantity surveyors, construction managers, engineers, project managers, architects, estate managers) in the construction industry.

This study aims to perform the bibliometric analysis of the customer engagement (CE) literature, highlights the major research themes and classifies the subdomains. The study also identifies antecedents and consequences, as well as dimension evolution, and suggests future research directions.

This study used a comprehensive bibliometric approach using Scopus data from 2002 to January 2024. Advanced analytical techniques, including bibliometric and cocitation analysis using R and bibexcel, were used. In addition, machine learning (ML)-based Latent Dirichlet Allocation (LDA) was used to extract latent themes.

This study reveals the domain’s past trend and present research scenario. The thematic analysis of CE is classified into three phases. Document cocitation analysis provided four broad clusters: conceptualization and operationalization, value creation through engagement, building relationships with brands and engagement-social media interface. The antecedents and consequences are categorized and presented along with the evolution of the multidimensional nature of CE.

This study adds to the literature in two key ways. First, the entire scholarly production has been compiled into one frame. Second, multiple methods were used to unravel citation, cocitation and textual data. Furthermore, ML-based LDA was used to extract latent themes from clusters and future research directions were proposed.

This paper aims to provide conceptual clarity on the different approaches of place branding in the literature. It discusses three main approaches and provides a new definition of place brands that acknowledges the full multi-sensory experience of place brands. This paper also elaborates brand management within the three approaches.

Conceptual paper

This study identifies three co-existing approaches of place branding and provides a definition of place brands for each of them. The first approach conceptualises place brands as symbolic constructs that identify and differentiate places from others. Brand symbols such as logos and slogans are central, assuming that brand meaning resides in them. The second approach views place brands as images and associations in the minds of target groups, whereby brands reside in individuals’ minds (the cognitive). This paper aligns with a third approach that views place brands as experiential, multi-sensory constructs. Brands invite not only mental representations in people’s minds but especially also multi-sensory embodied experiences. The authors thus define place brands as marketing systems that consist of dynamic performative assemblages of symbolic, discursive, institutional and material elements that selectively invite certain multi-sensory and embodied experiences of place by stakeholders and target groups.

This paper contributes to conceptual clarity by providing an analytical framework identifying three main approaches to place branding. The authors further reflect on the implications of each approach for brand management. This paper also builds on recent literatures to provide a new and contemporary definition of place brands as multi-sensory experiences that encompasses embodiment.

The purpose of this paper is to examine the life and work, both fiction and nonfiction, of the American author Upton Sinclair, for the purposes of better understanding his impact on management theory and practice.

Critical biography is a historiographical approach that analyzes aspects of an individual’s life events and the context that surrounds those events to better understand the contributions of an individual. In this case, this paper analyzes Sinclair’s biography, his work-related fiction and nonfiction and his interactions with business leaders and management thinkers of the day, including scientific management founder Frederick Winslow Taylor, auto industry leader Henry Ford and safety razor magnate King Gillette.

This paper identified four themes which are related to management and workplace history that pervade his fiction and nonfiction writing and link these events to the events of his life as well as the context of the times.

Although others have cited certain aspects of Sinclair’s work for specific purposes, this paper presents a systematic review of Sinclair’s broad oeuvre and its relevance to management and workplace history using a critical biography approach.

This study aims to discuss appropriate individual, organizational and macroleveled conditions when it is desired to foster intrapreneurship with nudge techniques.

Conceptual paper.

This paper aims to provide theoretical framework on the relationship between nudges approach and intrapreneurship and offer measurable propositions at different level of analysis for future research.

At the individual level it is theorized that nudges techniques on intrapreneurship will work when: “agents are aware of being nudged”, “choice architect is a well-recognized leader”, “perception of meaningful work is high” and “agents had former experience about being nudged”. At the organizational level it is claimed that the “number”, “type” and “frequency” of nudges plays the prominent role. Lastly, at the macrolevel it is postulated that “cultural adjustments”, “providing education” and “forming networks” sets the ground for pushing masses to intrapreneurial activities via nudges.

This pragmatic research paper aims to unravel the smart vision-based method (SVBM), an AI program to correlate the computer vision (recorded and live videos using mobile and embedded cameras) that aids in manual lifting human pose deduction, analysis and training in the construction sector.

Using a pragmatic approach combined with the literature review, this study discusses the SVBM. The research method includes a literature review followed by a pragmatic approach and lab validation of the acquired data. Adopting the practical approach, the authors of this article developed an SVBM, an AI program to correlate computer vision (recorded and live videos using mobile and embedded cameras).

Results show that SVBM observes the relevant events without additional attachments to the human body and compares them with the standard axis to identify abnormal postures using mobile and other cameras. Angles of critical nodal points are projected through human pose detection and calculating body part movement angles using a novel software program and mobile application. The SVBM demonstrates its ability to data capture and analysis in real-time and offline using videos recorded earlier and is validated for program coding and results repeatability.

Literature review methodology limitations include not keeping in phase with the most updated field knowledge. This limitation is offset by choosing the range for literature review within the last two decades. This literature review may not have captured all published articles because the restriction of database access and search was based only on English. Also, the authors may have omitted fruitful articles hiding in a less popular journal. These limitations are acknowledged. The critical limitation is that the trust, privacy and psychological issues are not addressed in SVBM, which is recognised. However, the benefits of SVBM naturally offset this limitation to being adopted practically.

The theoretical and practical implications include customised and individualistic prediction and preventing most posture-related hazardous behaviours before a critical injury happens. The theoretical implications include mimicking the human pose and lab-based analysis without attaching sensors that naturally alter the working poses. SVBM would help researchers develop more accurate data and theoretical models close to actuals.

By using SVBM, the possibility of early deduction and prevention of musculoskeletal disorders is high; the social implications include the benefits of being a healthier society and health concerned construction sector.

Human pose detection, especially joint angle calculation in a work environment, is crucial to early deduction of muscoloskeletal disorders. Conventional digital technology-based methods to detect pose flaws focus on location information from wearables and laboratory-controlled motion sensors. For the first time, this paper presents novel computer vision (recorded and live videos using mobile and embedded cameras) and digital image-related deep learning methods without attachment to the human body for manual handling pose deduction and analysis of angles, neckline and torso line in an actual construction work environment.