Abstract

Background
Depression results from interactions between biological, social, and psychological factors. Literature shows that depression is associated with abnormal brain structure, and that socioeconomic status (SES) is associated with depression and brain structure. However, limited research considers the interaction between each of these factors.
Methods
Multivariate regression analysis was conducted using UK Biobank data on 39,995 participants to examine the relationship between depression and brain volume in 23 cortical regions for the whole sample and then separated by sex. It then examined whether SES affected this relationship.
Results
Eight out of 23 brain areas had significant negative associations with depression in the whole population. However, these relationships were abolished in seven areas when SES was included in the analysis. For females, three regions had significant negative associations with depression when SES was not included, but only one when it was. For males, lower volume in six regions was significantly associated with higher depression without SES, but this relationship was abolished in four regions when SES was included. The precentral gyrus was robustly associated with depression across all analyses.
Limitations
Participants with conditions that could affect the brain were not excluded. UK Biobank is not representative of the general population which may limit generalisability. SES was made up of education and income which were not considered separately.
Conclusions
SES affects the relationship between depression and cortical brain volume. Health practitioners and researchers should consider this when working with imaging data in these populations.

Introduction

Mental health problems are significant public health issues within the UK and worldwide, with depression being one of the most prevalent. Research shows that there is a relationship between depression and brain structure (Tang et al., 2007; Kronmüller et al., 2009; Bos et al., 2018; Maggioni et al., 2019), and that social factors, including socioeconomic status (SES), are associated with both depression (Delgadillo et al., 2016; Marmot, 2010; Freeman et al., 2016) and changes in brain structure (Kweon et al., 2022; Colich et al., 2020; Jednoróg et al., 2012; Noble et al., 2015). However, these three factors are rarely all considered together. Given the impact of depression on both the individual and society, as discussed below, understanding the mechanisms of this disorder, to improve prevention and treatment options, is of critical importance.

Around 1 in 6 adults in England met the criteria for a common mental health disorder in the week prior to being surveyed (McManus et al., 2016). Mental health problems are one of the leading contributors to overall worldwide disease burden and are reported to account for 16 % of Disability Adjusted Life Years (DALYs, Arias et al., 2022). They confer substantial societal and economic implications with an estimated annual cost in England of £77 billion (Kirkwood et al., 2010). Depression is one of the most prevalent mental health problems, affecting approximately 5 % of adults (World Health Organization, WHO, 2023) and 280 million people globally (Institute of Health Metrics and Evaluation, 2023). Depression can be long-lasting with a single chronic episode, or recurrent, with many episodes over a long time, and has a substantial impact on an individual’s ability to function and cope with daily life. The risk of suicide is reported to be about 15 times higher in those with depression than the general population (Cipriani et al., 2005). This is however likely to be an underestimate as many who die by suicide have undiagnosed depressive symptoms.

Conclusion

This study is, to our knowledge, the first study to examine the relationship between depression, cortical volume, and SES in a middle-aged to older sample of this size. Given that SES appears to impact the relationship between depression and brain structure, we posit that SES should be a consideration for clinicians and scientists working with imaging data in these populations. Future research involving large-scale longitudinal data is needed to elucidate the causal relationships between the factors examined in this study.

Abstract

Business-to-business (B2B) suppliers need to develop specific capabilities to successfully manage digitalized touchpoints in B2B customer journeys. As digitalization leads to shifts in touchpoints, new demands arise regarding a supplier’s ability to manage these touchpoints. Developing capabilities for managing digitalized touchpoints is becoming a key aspect for suppliers in designing and managing attractive B2B customer journeys. Although extant research has highlighted the importance of managing touchpoints in the form of capabilities, this area has received surprisingly little research attention. Similarly, the B2B context in customer journeys remains under-researched. The present study investigates supplier capabilities for the management of digitalized touchpoints in B2B customer journeys. Through an exploratory in-depth case study, this research identifies seven key supplier capabilities for the management of digitalized touchpoints in B2B customer journeys: preparing customer resources, integrating customer resources, enabling collective actions, supporting customer actions, balancing activation levels, hybridizing environments, and merging digital environments. These capabilities are structured around a theoretically derived conceptualization of touchpoints as consisting of resources, actions, and environments. From a capability perspective, this study also demonstrates the key role of touchpoint control, as well as approaching touchpoints as sequences to ensure consistency across, and seamlessness between transitions of, touchpoints.

Introduction

The concept of customer journeys is increasingly recognized as a central element in marketing ( Homburg & Tischer, 2023 ; Steward, Narus, Roehm, & Ritz, 2019 ; Witell et al., 2020 ). A key building block in a customer journey is the notion of touchpoints, considered here as the interactions, or engagements, between a supplier and a customer ( Homburg, Jozić, & Kuehnl, 2017 ; Lemon & Verhoef, 2016 ). Because touchpoints are pivotal for, and embedded in, customer journeys, it becomes important for a supplier to be able to manage these ( Durmusoglu, McNally, & Chen, 2022 ; Hodgkinson, Jackson, & West, 2021 ). Poorly managed touchpoints can, for example, lead to excessive resource usage as well as bad customer experiences. A supplier’s ability to manage touchpoints becomes especially challenging in business-to-business (B2B) contexts, where customer journeys are characterized by greater complexity, a broader array of stakeholders and touchpoints, as well as longer engagement timelines ( Meyer & Schwager, 2007 ; Witell et al., 2020 ; Zolkiewski et al., 2017 ). These characteristics put added demands on the management of touchpoints but also highlight the need for further insights into B2B customer journeys ( Purmonen, Jaakkola, & Terho, 2023 ; Rusthollkarhu, Toukola, Aarikka-Stenroos, & Mahlamäki, 2022 ).

While existing research underscores the significance of touchpoints within the customer journey, and the competitive edge that can be gained through their effective management in the form of capabilities (e.g., Aichner & Gruber, 2017 ; Dhebar, 2013 ; Gao, Fan, Li, & Wang, 2021 ; Homburg et al., 2017 ), there is a notable lack of studies delving into the specific supplier-oriented capabilities necessary for managing these touchpoints ( Homburg & Tischer, 2023 ; Lemon & Verhoef, 2016 ; Maechler, Sahni, & van Oostrum, 2016 ). This is especially so in the face of advancing digitalization. Digitalization, describing the process by which digital technologies are influencing business processes (see, e.g., Li, Kannan, Viswanathan, & Pani, 2016 ), not only introduces new opportunities but also compounds the complexity of managing touchpoints ( Marino & Lo Presti, 2018 ; McColl-Kennedy et al., 2015 ). For example, both the diversity and number of touchpoints in a customer journey typically tend to increase as firms introduce digital technologies ( De Keyser, Verleye, Lemon, Keiningham, & Klaus, 2020 ; Larivière et al., 2017 ). This leads to an additional emphasis on understanding suppliers’ touchpoint management capabilities related to a new digital reality ( Ritter & Pedersen, 2020 ; Volberda, Khanagha, Baden-Fuller, Mihalache, & Birkinshaw, 2021 ).

Implications and future research

This study provides insights into the management of digitalized touchpoints in B2B customer journeys by operationalizing it as a set of capabilities. We add to existing literature by taking a supplier perspective on touchpoints, identifying seven capabilities to manage digitalized resources, actions, and environments, which together frame the management of digitalized touchpoints. We also provide guidance as to future research in the field of B2B customer journeys as well as for B2B managers in strategizing for customer journeys.

Abstract

Global virtual teamwork has emerged as a cornerstone of collaborative teamwork in today’s work landscape, characterized by cross-border collaboration using digital technologies. Although research has started to investigate the mechanisms underlying effective teamwork through information and communication technologies (ICTs), an often-neglected dimension is the pivotal social context within which this collaboration unfolds. To address this research gap, this study adopts a social capital lens on teamwork in proposing social capital as a multidimensional mediator between the usage of ICTs and team effectiveness. The research model was tested using questionnaire data from 271 technologically sensitive and aware companies in the DACH region (Germany, Austria, Switzerland). The findings reveal that using multiple ICTs alone does not suffice for effective global virtual teamwork. Therefore, this study highlights the significance of social capital for the effectiveness of global virtual teamwork, which holds significant implications for theory and practice.

Introduction

Advances in information and communication technologies (ICTs), coupled with the increasing prevalence of globalization, have driven organizations to rely on digital technologies for globally distributed collaboration—so-called global virtual teamwork ( Tavoletti & Taras, 2023 ). Due to several benefits, such as time and cost savings, talent pooling, and increased team diversity, global virtual teams were already well established in today’s workplace before the COVID-19 pandemic ( Jimenez, Boehe, Taras, & Caprar, 2017 ; Kozlowski & Ilgen, 2006 ; Tavoletti & Taras, 2023 ). However, global virtual teamwork also presents significant challenges that can threaten team effectiveness. Reliance on ICTs reduces media richness and delays feedback, including an increased risk of miscommunication and misunderstanding ( Bilotta et al., 2021 ; Klitmøller & Lauring, 2013 ; Mangla, 2021 ).

Based on the premise that a single medium cannot support the two fundamental communication processes of conveyance (i.e., sharing new information) and convergence (i.e., reaching a common understanding), we introduce the concept of ICT usage, which refers to the frequent and strategic use of multiple ICTs ( Dennis, Fuller, & Valacich, 2008 ; Niinimäki, Piri, Lassenius, & Paasivaara, 2012 ). We propose that high levels of ICT usage will increase team effectiveness, which consists of performance, longevity, and satisfaction ( Dennis et al., 2008 ; Hackman, 1987 ).

Conclusion

The confluence of digitalization and globalization has had an enduring influence on utilizing virtual and global collaboration in the workplace. Due to their embeddedness in a social context, teams are a focal point of multiple levels, linking the individual team members and the organizational system holistically ( Kozlowski & Bell, 2013 ). This requires a profound comprehension of the social context, which can enhance the uptake of ICTs and the effectiveness of global virtual teamwork. To fill this research gap, we conceptualized social capital as a multidimensional mediator, encompassing structural, cognitive, and relational social capital ( Nahapiet & Ghoshal, 1998 ), between the adoption of ICTs and team effectiveness composed of performance, satisfaction, and longevity.

In summary, this study provides a solid foundation for integrating social capital in global virtual teamwork. The results of our study indicate that frequent use of multiple ICTs does not influence the effectiveness of global virtual teams. Instead, a significant positive relationship was found between ICT use and social capital. Regarding the individual dimensions of social capital, this relationship was only found for structural social capital. Similar results were obtained for the mediator hypotheses, with both total and structural social capital acting as strengthening mediators between ICT usage and team effectiveness. Conversely, cognitive and relational social capital did not show significant mediating effects. The present research context makes developing cognitive and relational social capital difficult, although their importance cannot be denied, as both social capital and its individual dimensions show a positive relationship with team effectiveness. Possible ways to build cognitive and relational social capital include allocating sufficient time for team interactions and creating shared physical spaces, such as face-to-face meetings, to balance them. Overall, our study provides insights into the extent to which the integration of social capital enhances team effectiveness in today’s digitized and globalized world.

Abstract

This study investigated the determinants of financing decisions of firms from the Middle East and North Africa (MENA) region, particularly the effect of public corruption on financing decisions and the effect of disorder following the Arab Spring on public corruption-financing structure relationship. The study encompasses a total of 800 business entities from 14 different countries, spanning the time frame of 2005–2018. Data is analyzed through the application of static fixed effects and dynamic GMM-System models. Results indicate that large, tangible companies prefer debt, whereas profitable companies with more room for growth choose equity. Less corruption is associated with increased corporate debt. The use of debt decreased because of the Arab Spring, and corruption’s effect on leverage became weaker. The speed of adjustment to the target leverage is comparatively slow for book leverage, while it is significantly greater for market leverage. These outcomes are consistent with the pecking order behavior resulted from increasing information asymmetry, but the tradeoff theory has some support as well. The implications of this study entail the need for enhancing investor protection, strengthening control measures, increasing transparency, and fostering the overall growth of the financial system to facilitate enterprises’ use of debt financing, particularly in the post-Arab Spring era. This paper provides fresh empirical evidence demonstrating the effect of the Arab Spring on capital structure and on the relationship between country corruption and capital structure in the MENA region. The paper also expands the body of research on capital structure and corruption across countries by providing empirical findings from a region that has been relatively overlooked in previous scholarly works.

Introduction

Lack of a perfect capital market necessitates the need for capital structure (CS) policy [1, 2, 3, 4, 5]. The choice of debt and equity is important not only for stable corporate financial health but also for the role it plays in economic growth [6,7]. Since Modigliani and Miller’s [8] slice-of-the-cake argument, the literature has identified many firm-specific CS determinants [6,9] as well as macroeconomic factors [7,10, 11, 12]. Country corruption facets, such as weak regulations and inconsistent policies at the macro level, may affect financing decisions as they influence agency conflicts of interest, the risk of financial fraud, and resource waste at the business level [10,13]. Such consequences are exacerbated if accompanied by weak disclosure policies that enhance the information asymmetry problem and increase the cost of capital [14]. Consequently, financial market activity reduces as a result of investors’ low confidence.

Public corruption is a potential determinant of CS that is largely ignored. A common link is through asymmetric information as a result of ineffective management transparency, monitoring, and law enforcement [15]. This information gap is also caused by manager-shareholder agency conflicts [16]. Because of poor ruling systems and regulations, emerging countries are deemed more corrupt than developed countries [17]. Non-financial enterprises are less regulated compared with financial firms, and thus they are more exposed to corruption [18].

Conclusions

This study investigates the CS practices of non-financial companies operating in the MENA region. Country-level corruption and the Arab Spring’s effect on CS is analyzed through the application of static and dynamic models. Country corruption has an effect on CS because of the significant agency problems and information asymmetry that are associated with corrupt practices. The developing countries in the MENA region are more susceptible to corruption because of inadequate governance systems and regulations, which make them a suitable choice for this study.

Our contribution to the literature on capital structure is threefold. The study expands the research on CS across countries in a geographic area that has been relatively overlooked in previous scholarly works. Our second contribution is emphasizing the significance of enhancing institutional environments in developing countries to facilitate firms’ access to external finance, particularly when the level of corruption in a country is found to have a significant effect on the decisions that corporations make about their CS. Finally, addressing the effect of the Arab Spring, a period of political instability, on the CS decisions is the first instance in which such an analysis has been conducted. The findings of this research are likely to be significant to other developing countries and regions and carry major implications for emerging economies that share similar attributes.

Abstract

Terahertz (THz) and sub-terahertz (sub-THz) waves are unexplored waves between the infrared and microwave ranges. This range features unique characteristics of both light resolution and electromagnetic wave transmission. Sub-THz waves are part of attractive new diagnostic methods for inner objects because they are safer than normal non-destructive inspection methods involving high energy, such as X-rays. In this study, a novel non-contact and non-destructive inspection method for reinforced concrete (RC) structures using sub-THz reflection imaging is proposed to inspect the deterioration of inaccessible damaged RC structures. The results of this study confirmed that the proposed sub-THz imaging method can detect cracks and voids in concrete, as well as in metals inside or behind the concrete, based on differences in reflectance. In addition, the camera-based measurement system makes real-time on-site field measurements possible.

Introduction

In recent years, the deterioration of reinforced concrete (RC) structures has become an issue all over the world. Especially in Japan and other developed countries, large number of social infrastructures built during periods of rapid economic growth are aging significantly ( Alexander and Beushausen, 2019 ). The importance of appropriate maintenance management, including investigation and diagnosis, has been highlighted. In addition, from the perspective of a decarbonized society, it is desirable to avoid demolishing buildings and extend the service life of RC structures through necessary and affordable repairs. Thus, these considerations highlight a growing need for non-contact, non-destructive inspection methods to diagnose infrastructure deterioration without compromising performance. Furthermore, if remote inspection is possible, it is expected to improve measurement efficiency and expand the applicable areas. Therefore, a new inspection method that is not only non-destructive but also non-contact is required.

Several non-destructive and micro-destructive testing methods have been proposed for RC structures. For example, for internal defects that cannot be detected by visual inspection, some of the most widely used methods include percussion inspection ( Kazemi et al., 2019 ), ultrasonic flaw detection ( Lawson et al., 2011 ; Choi et al., 2016 ) and ground penetrating radar (GPR) ( Hugenschmidt and Mastrangelo, 2006 ; Chang et al., 2009 ; Laurens et al., 2005 ; Liu et al., 2020 ; Wiwatrojanagul et al., 2017 ). Table 1 shows a comparison between these methods. During percussion inspection, the concrete surface is knocked, which makes it possible to infer the state of internal deterioration based on the difference in the echo sound. In the case of ultrasonic waves, also a type of elastic wave, it is possible to measure the location of cracks and rebars inside concrete due to differences in acoustic impedance inside the material. Using GPR makes it possible to probe embedded rebars and voids inside concrete owing to its high penetration depth. However, these methods require contact with an object to be measured, which causes measurement problems at elevated or generally inaccessible places, thus highlighting the need for developing a method that can inspect the interior of concrete without contact.

Conclusion

In this study, we conducted measurements using a sub-THz camera to simulate embedded rebar and defects on the surface and inside concrete, assuming that a non-destructive inspection method using sub-THz waves will be applied to reinforced concrete structures. We then conducted actual measurements on real structures. The findings are as follows:

1) An aluminum tape placed on the back of the specimen to simulate the embedded rebar was detected up to 20 mm thickness of the specimen.

2) Field measurements at 10 GHz indicated the possibility of exploring rebars with a cover thickness of approximately 30 mm.

3) In the measurement of specimens with slits simulating cracks, detection was possible for slit widths greater than 1 mm.

4) Even when the slit was hidden by placing a 5-mm-thick mortar, detecting a slit up to 2.5 mm was possible.

5) The reflectance and transmittance varied sensitively with frequency. This fact indicates the potential for more detailed measurement with the selected appropriate frequencies. Further studies are needed to establish their relationship.

6) Camera-based measurement enables areal measurement and real-time monitoring.

7) Downsizing and weight reduction of the measurement system improved its transportability, confirming the possibility of measuring real structures.

Abstract

This research project developed a framework for assessing digital transformation (DT) maturity in large government-owned corporations (GOCs), focusing on integrating building information modelling (BIM), digital engineering (DE) practices, value of information, data integration aspects, and critical information management competencies, relating to asset management, asset delivery, and asset performance. Recognising DT’s strategic importance in asset lifecycle management, researchers created a practical DT maturity assessment tool applied to an Australian GOC. The framework and Excel assessment tool outline DT maturity across seven categories and 56 indicators, using the analytical hierarchy process (AHP) to rank indicators based on expert input. The tool enables straightforward data input and DT maturity evaluation, helping organisations understand their current DT status and set improvement targets. Workshops with DT professionals validated the tool’s effectiveness through a case study, offering insights into DT maturity levels and a roadmap for technological integration and data-driven decision-making. The research highlights DT’s role in enhancing efficiency, innovation, and safety, emphasising the need for strategic alignment with organisational objectives.

Introduction

The building and infrastructure industries are gradually transitioning towards building information modelling (BIM) as an object-based digital representation of an asset’s physical and functional characteristics [1], [2] and digital engineering (DE) practices to enable more productive methods of planning, designing, constructing, operating, and maintaining assets, using digital processes [3]. As detailed later in the paper, “digital” encompasses approaches, tools and technologies such as BIM and DE together with data science, the Internet of Things (IoT), and AI solutions integrated to digitise assets throughout the lifecycle. Asset owners recognise the importance of digital transformation (DT) in delivering and managing assets [4], as it offers many benefits throughout the asset lifecycle and can enhance efficiency, value for money, productivity, innovation, and safety.

1.1. DT of large infrastructure asset ownersGovernments and government-owned corporations (GOCs) are typically owners and operators of large assets, such as buildings, infrastructure, and other asset holdings across the spectrum of services. Governments and industries must transition from ‘digital by exception’ towards ‘digital by default’ [5], [6]. The infrastructure sector should adopt an evidence-based approach to infrastructure planning, delivery, and operations, including BIM, DE, embedded sensors, and digital asset management [7]. DT offers significant potential value and benefits to government agencies that manage assets across the whole-of-asset lifecycle. DT can assist in strategic investing and partnering with local governments and industry to deliver more benefits, including [8]:

Conclusion

The dynamic evolution of the building and infrastructure sectors towards digitalised practices underscores the growing importance of asset owners engaging in comprehensive DT. This research project has developed a multifaceted framework for assessing DT maturity tailored to the needs of large GOCs.

The existing assessment tools and methods have been reviewed for suitability in assessing the DT in whole-of-life asset owner organisations. The reviewed tools offer varying assessment scopes, including a capability assessment, maturity assessment, and benchmarking. The need and potential benefit of a new maturity assessment tool that would balance assessment accuracy and completion efficiency were established based on the shortcomings and limitations of existing DT maturity tools and methods. The key contributions of the new DT maturity assessment framework and tool developed by the research team include (i) a holistic view on the assessment of how well organisations use data and digital solutions, focusing on BIM capabilities, the value of information, data integration aspects, components of the smart city concept and critical information management competencies; (ii) an evidence-based scoring approach including assigning weight to various assessment indicators based on their importance to ensure the accuracy of the assessment; (iii) a multiperspective assessment allowing for more accurate organisation-wide analysis; (iv) short-term and long-term recommendations based on the current and target levels gap to facilitate performance improvement while realising the benefits and value of getting to each maturity level.

Abstract

The Internet of Things (IoT) leads to the next phase of human interaction with technology. With the help of the IoT, physical objects can be given the ability to generate, receive, and seamlessly trade data with one another. The IoT includes a wide variety of applications, each of which focuses on automating a specific task and works to give inanimate objects the ability to act independently of human intervention. The currently available and upcoming IoT applications hold a great deal of promise for enhancing the level of convenience, productivity, and automation enjoyed by users. High levels of security, privacy, authentication, and the ability to recover from attacks are required for the implementation of such a world in a manner that is constantly expanding. In this light, it is necessary to make the necessary adjustments to the architecture of IoT applications to accomplish end-to-end security in IoT environments. In this article, a comprehensive review of the security-related challenges and potential sources of danger posed by IoT applications is provided. Following a discussion of security concerns, a variety of new and established technologies that are focused on achieving a high degree of trust in the applications of the IoT are covered. Machine learning, fog computing, edge computing, and blockchain are just a few of the technologies that help the IoT provide greater security.

Introduction

The Internet of Things (IoT) is one of the disruptive technologies of the 21st century that has revolutionized every business dimension across the globe. The Internet has become an essential component in daily activities such as e-commerce, e-learning, e-conferences, etc. According to [1], the number of IoT devices deployed may exceed 21.3 billion by 2022. Intelligent interfaces connect IoT devices in order to collaborate, gather, communicate, and store data. Deploying IoT devices enhances business productivity by optimizing operational procedures and maximizing the utilization of available resources. IoT brings innovation in the way things are monitored and managed remotely with the help of real-time data acquired from the sensors. With the unrestrained volumes of data generated by billions of connected devices, storage, management, and security are arduous. Security aspects such as authentication, authorization, privacy, confidentiality, availability, and integrity form the basis for information exchange in a trusted environment. Authentication is the process of identifying the genuineness of an entity. The authorization process allows only authenticated users to access the resources. The protection of privacy prevents hackers from accessing the user’s private information. Data confidentiality is an outcome of authentication and authorization. It prevents sensitive data from being reclaimed and exploited. A device’s availability confirms that IoT devices and services are resilient to attacks and are accessible all the time. Data integrity is the process of providing a tamper-proof platform for information communication, exchange, and storage.

Conclusion and future directions

In this paper, the methods that are currently available in the literature are discussed, and this paper also presents the methods that are currently available. The subsequent step is an in-depth discussion of the numerous security risks and the importance of threat modeling. The subsequent topic is a discussion of the various IoT applications’ necessary security precautions. It reviews the prior research on the numerous security issues and the solutions put forth by various researchers. The holes that were found while conducting this literature review served as inspiration for the current research work.

7.1. Research challenges
The billions of IoT devices deployed across the globe collect personal and sensitive data and exchange it with other networks using intelligent interfaces. Providing device authentication, authorization, data privacy, and security in such an un trusted environment is a challenge. Centralized trusted infrastructure cannot scale to the dynamic and ever intensifying traffic and, thus, leading to bottlenecks in the network. Distributed authentication can scale to the increasing demands of the IoT networks, but requires distributed trusted systems. The majority of the work in the IoT security domain focuses on embracing the security mechanisms of WSNs and conventional Internet-based applications. However, these mechanisms are far from being implemented in real-time scenarios due to the specific challenges of IoT, such as

Abstract

Due to the industrial revolution and, thereby with, the emergence of Industry 4.0, there has been an impact on the marketing of business firms, enabling them to digitally transform and adopt Marketing 4.0 practices supported by smart technologies. One of these is Big Data Analytics (BDA), which enables a firm to improve its marketing practices. The main objective of this study is to evaluate how integrating big data technology improves the marketing strategies of Indian FMCG companies operating in a dynamic and highly competitive market distinguished by its size and diversity, constantly changing consumer behaviour, and Marketing 4.0 trends. This study adopts a systematic approach to coding an interview with seasoned Indian FMCG professionals to explain the capabilities of Big Data in molding marketing practices. A framework is constructed based on the same. The theoretical and practical implications are discussed to visualize its applicability in business. Further, the Resource-based View (RBV) theory is discussed for describing the insights into the role and adoption of Big Data by Indian FMCG firms for enhancing performance and achieving competitiveness, along with demonstrating its benefits for decision-making, customer loyalty and internal capability assessment.

Introduction

With technological advancements, industries now utilize innovative technologies that bolster a range of corporate activities and procedures, profoundly influencing the internal operations of these firms. (Cammarano et al., 2023, Singh et al., 2022b). The fourth industrial revolution, known as Industry 4.0, which is driving this technological change for business firms, serves as a bridge between intelligent products and adaptive processes and has a significant impact on both business models and production processes (Rosário & Dias, 2022; Salkin et al., 2018). Industry 4.0 enables the digital transformation of firms, which is further impacted by different internal and external factors related to the firm. The digital transformation is required to improve customer experiences and retain customers (Kitsios et al., 2021). Despite their implementation challenges and hazards, these advancements increase market analytics, cost, channel management, client connections, professional skills, and organizational procedures (Pascucci et al., 2023). With Industry 4.0, there is a steady trend towards understanding the consumers, which includes their needs, behaviours, storytelling, and anticipation (Lampropoulos, 2023; White & Pathak, 2023). These are the core components of marketing techniques that have evolved into marketing 4.0 (Yakut, 2022). As an outcome of the emergence of trends like Big Data (BD), social media, corporate social responsibility, and e-commerce, the shift to Marketing 4.0 is accelerating (Guven, 2020). Marketing 4.0 is driven by the convergence of offline and online marketing strategies and incorporates technical advancements to provide better flexibility (Rathod et al., 2020; Kotler et al., 2017). The improvement of the consumer experience, the induction of repurchase intention, and brand promotion are some of the significant achievements of Marketing 4.0 (Dash et al., 2023). Consumer usage patterns of social media, online platforms, search engines, contextual interactions, and community influences are some of the areas the companies are looking into. Companies use the information mainly for promotional and consumer engagement activities. The consumers are seen to be transformed into advocates through marketing 4.0, where a sense of community building takes place, resulting in a meaningful engagement of the marketers and consumers (Gau, 2019).

Conclusion

This study discusses and examines the role of BD and how an FMCG firm can adopt BD to improve its overall performance and attain a competitive position in the market. This research is the first of its kind to explore the implications of BD in the Indian FMCG sector. The relationship among BD, marketing practices and FMCG from in Indian perspective is a unique contribution to this paper. In addition to its usefulness, the study explores the crucial roles that automation and decision science play. This study discusses the benefits the firm achieves for accepting BD in the business. The study reveals some of how BD helps in decision-making for FMCG firms. For Indian FMCG firms, BD is crucial to value creation and achieving business operations’ scalability. FMCG organizations are using BD and analytics solutions more and more since they help create value, scale corporate operations, and increase output in today’s competitive market. BD makes it possible to analyze consumer preferences and behaviour at each transaction stage with a business. FMCG companies may now provide personalized experiences through targeted messaging, unique offers, and channel-specific communication optimization. BD also offers in-the-moment customer insights via sentiment, preference, and behaviour research, which aids FMCG companies in creating goods that enhance customer experiences and provide them with the necessary competitive edge.

Additionally, BD facilitates effective market campaigns through real-time predictions, data processing, and analysis. BD can also be strategically used through automation, new business model innovation, decision science, and risk management. Furthermore, customer segmentation based on BD makes marketing techniques more effective, and real-time customer insights, like sentiment analysis and tracking of consumer preferences and behavior, help organizations respond quickly to market changes.

Abstract

Purpose
This study proposes and tests the effectiveness of an integrated approach to community-based internal branding (CBIB) in a business-to-business setting. It integrates classical and contemporary views on internal branding, integrating community-building activities into the proposed internal branding framework ensuring a holistic model of co-creation of a corporate brand identity. It also examines the moderation effect of employee’s personal, job, and community-related characteristics on the relationships in the proposed model.

Design/methodology/approach
This paper presents a detailed narrative review to propose a conceptual model and uses a quantitative research design to test a set of hypotheses using structural equation modeling on 400 responses collected through a survey.

Findings
This study finds that integrated CBIB is a viable approach for implementing internal branding. The effectiveness of building employee brand commitment is demonstrated through the testing of the model. We also find that employee’s age, gender, organizational tenure, membership duration (in the brand community), education level, customer interaction, leadership status, and participation in brand fests moderate the proposed relationships in the CBIB model.

Research limitations/implications
One key limitation of this paper is that it lacks the multi-cultural and multi-industry perspective, which, given promising results in the current context, may be investigated in future studies.

Practical implications
The paper proposes a community mode of implementing internal branding in a B2B setting and suggests a way to create brand champions across the organization.

Originality/value
As per the authors’ knowledge, this paper is the first quantitative investigation of integrated community-based internal branding.

Introduction

A brand must deliver its promise (Burmann & Zeplin, 2005) or the effort that goes into market research, positioning, and creation of brand identity is likely to be lost (Baumgarth & Schmidt, 2010). No doubt, the internal branding philosophy of a firm directly influences its brand image (Mäläskä, Saraniemi, & Tähtinen, 2011). In business-to-business (B2B) and service firms, front-line sales employees, and support staff are key to delivering brand experience to the customer. Further, large B2B firms, due to their extensive employee base, complex structure, and multi-national spread, are at a greater risk of presenting mixed brand messages (Lee, 2021; Martin, 2021).

Research in the areas of internal branding, and organizational behavior reveals that a strong brand identity may be built by treating employees as internal customers (Baumgarth & Schmidt, 2010; Berry, Hensel, & Burke, 1976; Grönroos, 1985, Grönroos, 1997). Despite this assertion, when it comes to the implementation of internal branding in the B2B context, the classical view of internal branding recommends a top-down approach (Iglesias, Landgraf, Ind, Markovic, & Koporcic, 2020). The brand identity is fixed and strongly controlled by the firm, and is unidirectionally communicated to external stakeholders (Iglesias et al., 2020; Kapferer, 2012). On the other hand, the contemporary school of thought is shaped by the proliferation of digitalization and the internet, and it highlights the limited efficacy of a control-driven, top-down internal branding in the current B2B landscape (Iglesias et al., 2020; Iglesias, Ind, & Schultz, 2022; Saraniemi, 2022). At the core of this school of thought is the idea that brand identity is fluid, and is constantly co-created and developed through active conversation with all stakeholder groups across corporate brand interfaces (Iglesias et al., 2020; Iglesias et al., 2022).

Results

4.1. Measurement model
Assessment of the conceptual model (Fig. 2) includes testing the measurement model, structural model, mediation, and moderation analyses, all of which are undertaken using SPSS AMOS 26. All fit indices for the measurement model, viz., χ2/df = 2.160, CFI = 0.950, TLI = 0.942, and RMSEA = 0.054 are acceptable (Hair et al., 2010). We also performed the equivalence testing of the measurement model recommended by Marcoulides and Yuan (2016) by calculating the T-size RMSEA and CFI values. The T-size calculates the minimum population CFI and maximum size of misspecification (T-size RMSEA). We find that T-size RMSEA and CFI in equivalence testing are 0.059 and 0.935 respectively (against the conventionally reported value of 0.054 and 0.950). The cut-offs for T-size for the RMSEA and CFI based on the degrees of freedom (349), sample size (400) and number of observed variables (29) are:

Abstract

This research explores earnings quality as a quality measurement of optimism and trust in future returns, where the highly sustainable business has driven up obedience and compliance as a sign of prudent and consistent accounting policy. Manipulation activity is a widely open chance for opportunistic motives, associated with low certainty as a handicap to estimate high accuracy future returns. All observations in the Indonesia-listed manufacturing companies occurred from 2010 to 2022; this causal research uses moderated regression with the dummy variable in testing hypotheses and robust checks. This purposive sampling research has 154 companies with an unbalanced panel; two testing models on equity and earnings are used as sensitivity testing of positive perception. The high-prospected firm pointed out the persistent willingness to implement positive earnings management with this high consistency accounting treatment, which has been transformed into no violation. A positive correlation exists between high earnings quality and future returns, including concentration on real earnings as symbolized by a rational decision model. High-quality accounting information is valid information in predicting the going concerned, linked up to anticipating the peach-lemon effect, where business growth and dividends are used as a signaling effect. This centralized one-platform of the financial reporting system and going private is aimed to minimize the chance of misleading information and anticipate the low-prospected. The highly prospective has high consistency accounting treatment and proper tax management as the validated sustainability indicator, and the rationality modeling is modified from the simplex-linear programming as simulative modeling concerning the Decision Tree and Bayes Theorems.

Introduction

As proven by some empirical research last decade, high-quality financial reporting has been a crucial prerequisite for investors to monitor and check the capability of management to reach better prospects. The decision usefulness of accounting information is meaningful information because of the high obedience to the regulation (i.e., González-Sánchez et al., 2023; Jian et al., 2023). Structural knowledge of real earnings has recognized that consistency and prudent accounting have connected constructively with the market price movement; inevitably, this adverse signal pointed to a low probability of reaching a highly sustainable business model (i.e., Rezaee and Tuo, 2019; Park et al., 2021). Ping (2016) accentuated that low accruals positively impact investor perceptions with no chance of abnormal returns as a dysfunctional function. Therefore, earnings quality exists as a high–accuracy guideline of optimism and confidence as a decisive standpoint in calculating the expected returns when the volatile movement of agency cost has been a destructive consequence of sustainable performance; subsequently, this pragmatic evidence is reinforced by Akbari et al. (2019), Uzezi (2022), Beardsley et al., (2023), and Al-Asfour and Abu Saleem (2023)), underlining the proper tax management has been prioritized for keeping on the investor’s faith and belief.

The dividend is a “puzzle”, reflecting a myopia perspective of designing this payout policy as optimism of future growth opportunities (i.e., He et al., 2017; Alghazali et al., 2023; Sikalidis et al., 2023), Sidhu et al. (2023) found this payout policy measures the managerial capability of keeping on the business sustainability, particularly in anticipating the financial distress. The prominent role of the signaling effect is to smooth the unpredictable movement of market price, signifying the high risk; this research found a classic phenomenon of high-yielded dividend policy as a gap of research, where the annual average dividend payout ratio is higher than sales and earnings growth. In practice, the pattern of this payout policy has been explored in the Indonesia Capital Market, considering the magnificent performance as number 4 worldwide and the highest index growth in the Southeast Asia region area; accurately, the representative data distribution can be used to generalize the current circumstances of the signaling effect (see Appendix 1 Table 6). Concerning the manufacturing industry sector as an ultimate attractiveness in this capital market (see Appendix 1 Table 7), this sector had extraordinary growth during the Pandemic, representing an irrecusable occurrence. An annually detailed average comparison between the dividend payout and the business growth of sales and earnings is depicted in Fig. 1 below.

Conclusion

These results can be concluded; firstly, earnings quality had tested positively on investor perception when it covered up obedience and compliance. Manipulation activity and tax management are critical P(MAQ, H|DTAQ.Hi)x P(MAQ, H) P(MAQ, H|DTAQ, Hi)x P(MAQ, H) + P(MAQ, H |DTAQ, Lo).x P(DTAQ, Lo) M. Siladjaja and J. Jasman Journal of Open Innovation: Technology, Market, and Complexity 10 (2024) 100191 10 measurable factors in predicting high future certainty; the prudent accounting treatment reflects high consistency in publishing high earnings quality. Secondly, the dividend is used as the most effective signaling effect, which affects earnings quality differently; the positive contribution to earnings quality is a guideline for efficient contracting. Conversely, tax management and dividends have been connected to an exclusively mutual relationship aimed at smoothing the internal conflict intensity; nearly, the management is concerned with the dividend in obtaining a low cost of capital as an absolute comparative advantage. The high sales growth is an indicator of going concern, which is tested to drive up higher obedience and compliance; the high-prospected firm is assured of a highly sustainable business model, including high compliance with a minimum chance of agency costs and tax exposure. Finally, the high rationality perspective illustrated the conceivably interactive feedback between management and investors in predicting each party’s decision precisely as a comprehensive illustration of positive earnings management as optimism and confidence in the future.

The pattern of earnings management has various methods for calculating the residual error as a predictive signal of obedience and compliance because running fair value measurement is acknowledged internationally as a principal-ruled accounting standard. Commonly, the same perception of accounting treatment can be formed worldwide. The testing on the manufacturing-industry sector shows the practical implication for all regulators who must continuously monitor the business sustainability regarding the trust in this capital market. Implicitly, this calculation model can be implemented in other countries when earnings management has been tested as an open chance of discretionary behavior in reporting the actual performance; both consequences of efficient contracting and opportunity motives as a leading role of signaling effect have a critical influence on illustrating the real earnings management, covering up obedience to accounting standards and compliance with tax regulation. When the prospect theory pushes the positive contribution on the expected future returns, it is a challenge for this research to prove this theory; hence, this predictive simulation has been proposed with simplex-linear programming in calculating the maximum returns and minimum cost,

Abstract

     One of the main challenges in the design of wireless ad-hoc and sensor networks is to reduce energy consumption and radio interference and collision, which are strictly and strongly correlated to the transmission range of the nodes. In this article, the transmission ranges of sensors in sparse Wireless Sensor Networks (WSN) is theoretically analyzed and is shown that the transmission ranges of sensors can be significantly reduced in this type of WSNs without losing any connection. Next, a method is presented to calculate reduced transmission ranges. In this method, an iterative transmission range adjustment mechanism is used to select an almost transmission range while no information is needed on the location of nodes or the distance between nodes. This method is very efficient and its communication overhead is low. It can be used as a pre-step of any routing algorithm in order to decrease energy consumption and radio interference in targeted scenarios. The simulation results show the efficiency of the proposed method. We got at least 50% improvement in energy consumption in comparison with full power network, in sparse WSNs.

Introduction

     Wireless Sensor Networks (WSNs) have become increasingly popular in recent years, as they offer a powerful and cost-effective solution for monitoring and collecting data from a variety of environments. A Wireless Sensor Network (WSN) consists of a large number of distributed sensor nodes that cooperatively monitor the physical world [1]. Each node in these networks is typically equipped with a wireless communication device, a small microcontroller, a memory unit and a power source. The nodes in a WSN are typically battery-powered and have limited processing power, memory, and communication bandwidth. Therefore, the design of a WSN requires careful consideration of these constraints, such as the choice of communication protocol, data routing algorithms, and energy management strategies [2].

     The complexity of the WSN domain as well as the presence of many sensor nodes unavoidably introduces a large amount of data in these networks that must be processed, transmitted and received. The sheer amount of data generated by WSNs can pose a significant challenge for the network design and operation. The sensors in a WSN can generate data continuously or periodically, depending on the application requirements. This data must be processed, stored, and transmitted to the base station in a timely and efficient manner. So the complexity of the WSN domain and the presence of many sensor nodes can introduce a large amount of data that must be processed, transmitted, and received [3]. Despite their profound advantages, the utilization of WSNs is often battery-powered and strictly limited due to energy constraints. In fact, most of the energy expenditure of a sensor node occurs during wireless communication, and the remaining energy is consumed during sensing and data processing. The radio transceiver of a node consumes a significant amount of energy during data transmission and reception. Therefore, the energy consumption of a node must be carefully managed to ensure the longevity of the network [4]. Transmission power adjustment for a special transmitter-receiver pair depends on several environmental conditions. The transmission power required to reach the receiver is affected by two main factors including distance and wireless connection quality. Distance affects transmission power. As the distance between the transmitter and receiver increases, the signal strength decreases, resulting in a weaker connection.

Conclusions and future works

     We studied the transmission range of sensors in wireless sensor networks in this study, and proposed a simple yet effective distributed transmission power control algorithm for sparse wireless sensor networks. We showed that this algorithm has advantages in many cases. The main idea of algorithm is simple, but performance of algorithm in targeted scenarios is excellent. We analyzed the performance of this method theoretically and show that using this method is worthwhile in some scenarios, especially in sparse wireless sensor networks with high amount of communication traffic. In these scenarios, our method can be used as a pre-step of any routing algorithm and decrease energy consumption and radio interference. As a future work, we intend to design methods to overcome the collisions problem. Designing methods for resisting the algorithm against the sensor failures is another future work. Furthermore we intend to work on using learning methods like Reinforcement learning for power control. Designing a good energy efficient reward mechanism is one of the main challenges of these methods.

Abstract
This paper examines the relation between bank profit performance and business models, using a machine learning–based approach. The analysis contributes to the literature on this relation by considering the bank portfolio’s ability to yield profits as the identification criterion of strategic profiles and by including all the components of the business model simultaneously in the identification process. Our research strategy is applied to the European Union banking system from 1997 to 2021. The paper’s primary finding indicates that specialization seems to be a strategy that results in banks adopting business profiles with better profit performance, particularly if the banks specialize in the standard retail-oriented model.

Introduction

      What characteristics of bank business models enhance profitability? The search for answers has been among supervisory authorities’ priorities since the end of the Great Recession and is likely to maintain its relevance in the aftermath of the COVID-19 pandemic. The reasons for such interest lie in the fact that the relation between business models and profitability can reveal the viability of banks’ strategic plans and, hence, the viability of banks themselves. In this regard, the Anon (2016) links poorly adapted business models to low bank profitability in advanced economies, identifying the former as an eroding agent of bank resilience over time. However, concern about the profitability of banks’ business profiles has been especially strong in the European Union (EU), as reflected by the fact that the European Central Bank launched a thematic review in 2016 to assess the relation between profitability and business models (European Central Bank, 2018).

      Banking research has examined this relation in two broad and different ways, using regression analysis to explore the effects of the characteristics of the bank business profile on profitability or grouping banks into business models by means of clustering techniques.

Conclusion

     The ability of business models to generate profits is an ongoing concern for banking authorities, especially in the EU. Closely related to this concern, we propose a new methodological strategy to identify business models and to assess their relation to profit performance. Previous works on business models have assumed the business models as a given or have identified them using similarities in balance sheet components. In either of these cases, profit performance is a byproduct of the business model. By contrast, in our identification strategy, profitability is at the core of the definitions of banks’ strategic choices. In particular, business models are obtained using the contributions of the bank portfolio components to profitability as the instruments of clustering analysis.

      The empirical exercise focuses on the EU banking system in 1997–2021. According to the classification of business profiles based on their overall contributions to profit performance, the best profile is a standard retail-oriented model, the second-best one is a standard wholesale model, and the worst profile, which has only equity as a characteristic component, does not match any standard model. Therefore, specialization seems to be a strategy that results in banks adopting business profiles that perform better in terms of their contributions to profitability, particularly if the banks specialize in the standard retail-oriented model.

Abstract

     Green innovation is an essential and burning topic for environmental and organizational performance. Therefore, this research aims to examine the effect of green innovation on environmental performance, which leads to organizational performance. Another objective is to measure the impact of two dimensions of green innovation, such as green process & green product measures, on green innovation. The second prime aim of this research is to evaluate the moderation of management commitment & human resource practices in an association between green innovation and organizational & environmental performance. A total of 320 employees provided their perspectives on a self-administrated questionnaire from the textile industry of Pakistan. We have employed SEM-based multivariate modeling to examine the data. This research has measured the reflective indicators measurement model through confirmatory factor analysis, an obvious choice of structural equation modeling to examine observed and unobserved variables and indicators using PLS-SEM (partial least square-structural equation modeling). The research findings reveal a positive & significant effect of product & process innovation on green innovation. Further, green innovation significantly impacts environmental and organizational performance. A two-way interaction (moderation) of human resource practices & green innovation does not have a cogent moderating effect on organizational & environmental performance. However, management commitment has a significant moderation between green innovation & organizational performance. A three-way interaction (moderated moderation) model finds a substantial effect on organizational attainment but an insignificant impact on environmental performance. The research outcomes significantly contribute and suggest that practitioners and policymakers must institutionalize green innovation practices in their organizations to enhance their organizational and environmental performance. HR practitioners play a vibrant role in creating green norms and organizational culture. The study findings also suggest that management commitment to green innovation advocates organization-level transformations toward adopting green practices.

Introduction

     With the advent of technology and scientific advancements, the world has provided immense exposure to artificial resources, making life leisurely. However, artificial resource opulence has come at the cost of sustainability and the environment. The world has thus been facing issues with balance acquisition between sustainable usage of resources and economic development [1,2]. Managing both have been a great concern for the economies as one comes at an expense and tradeoff. Researchers have observed that economic growth and sustainability cannot go together [3,4]. Green growth and general innovation are well recognized for their interrelationship [5]. It is essential to observe that national economic development is established through soaring industrial activities [6]. In this essence, Segerstrom [7] validated through his proposed model that firm-level innovations immensely support economic growth. Green innovation is beneficial to prevent the environment from pollution, help in recycling waste, and could also save non-biodegradable energy [8,9]. Moreover, green technologies could achieve sustainable development [10,11]. In order to implement and achieve the target of green innovativeness, firms need to adopt teamwork within their organizational ecosystems (Muisyo et al., 2022). The said process can be run by key parameters such as the organizations’ access to large-scale data, the commitment of the management, and proper usage of human reserves [12,13], among other considerations. The outcomes demonstrated that firms are enticed to accept green innovation practices when internally and externally motivated organizations. Internal motives combine management’s commitment and supplier’s partnership, whereas external motives are regulations and demand pressures from customers. Thus, there is a direct relationship between the two [14]; (Parmar et al., 2022). Organizations can enhance their performance through green innovation as green practices guide them to devise strategies that can help them use fewer resources, reduce the chances of harm, and create a carbon footprint in the organization [15]. The green revolution is a unique strategy that permits organizations to create new techniques and systems that help organizations enhance their performance [16,17].

Conclusion 

     This study evaluated the connotation between green product & process innovations and green innovation. Moreover, the study examined the impact of green innovation in affiliation with organizational & environmental attainment. The study’s findings explored all the hypotheses devised to meet study objectives. Moderation effects of management commitment towards greening and green human resource practices were also examined between the primary relationship. Primary responses were obtained from the mid-career and upper management of the textile sector of Pakistan. This research revealed that product & process innovations have a cogent and affirmative effect on green innovation. The findings further demonstrated that green innovation exerted an affirmative and cogent effect on organizational & environmental performance. Thus, the senior management should seriously consider green innovation projects to increase the firm’s environmental performance and the long run, sustainable competitive growth. While evaluating the moderating effect of HR practices on environmental attainment, the findings are not supported.