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The advancements in internet technologies and the use of sophisticated digital devices in supply chain operations incessantly generate enormous amounts of data, which is termed as big data (BD). The BD technologies have brought about a paradigm shift in the supply chain decision-making towards profitability and sustainability. The aim of this work is to address the issue of implementation of the big data analytics (BDA) in sustainable supply chain management (SSCM) by identifying the relevant factors and developing a structural model for this purpose.

Through a comprehensive literature review and experts’ opinion, the crucial factors are found using the PESTEL framework, which covers political, economic, social, technological, environmental and legal factors. The structural model is developed based on the results of the total interpretive structural modelling (TISM) procedure and MICMAC analysis.

The policy support regarding IT, culture of data-based decision-making, inappropriate selection of BDA technologies and the laws related to data security and privacy are found to affect most of the other factors. Also, the company’s vision towards environmental performance and willingness for material and energy optimization are found to be crucial for the environmental and social sustainability of the supply chain.

The study is focused on the manufacturing supply chain in emerging economies. It may be extended to other industry sectors and geographical areas. Also, additional factors may be included to make the model more robust.

The proposed model imparts an understanding of the relative importance and interrelationship of factors. This may be useful to managers to assess their strengths and weaknesses and ascertain their priorities in the context of their organization for developing a suitable investment plan.

The study establishes the importance of BDA for conservation and management of energy and material. This is crucial to develop strategies for enhancing eco-efficiency of the supply chain, which in turn enhances the economic returns for the society.

This study addresses the implementation of BDA in SSCM in the context of emerging economies. It uses the PESTEL framework for identifying the factors, which is a comprehensive framework for strategic planning and decision-making. This study makes use of the TISM methodology for model development and deliberates on the social and environmental implications too, apart from theoretical and managerial implications.

This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.

This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.

This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.

Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.

Human-induced marine environmental noise, such as commercial shipping and seismic exploration, is concentrated in the low-frequency range. Meanwhile, low-frequency sound signals can achieve long-distance propagation in water. To meet the requirements of long-distance underwater detection and communication, this paper aims to propose an micro-electro-mechanical system (MEMS) flexible conformal hydrophone for low-frequency underwater acoustic signals. The substrate of the proposed hydrophone is polyimide, with silicon as the piezoresistive unit.

This paper proposes a MEMS heterojunction integration process for preparing flexible conformal hydrophones. In addition, sensors prepared based on this process are non-contact flexible sensors that can detect weak signals or small deformations.

The experimental results indicate that making devices with this process cannot only achieve heterogeneous integration of silicon film, metal wire and polyimide, but also allow for customized positions of the silicon film as needed. The success rate of silicon film transfer printing is over 95%. When a stress of 1 Pa is applied on the x-axis or y-axis, the maximum stress on Si as a pie-zoresistive material is above, and the average stress on the Si film is around.

The flexible conformal vector hydrophone prepared by heterogeneous integration technology provides ideas for underwater acoustic communication and signal acquisition of biomimetic flexible robotic fish.

The purpose of this study was to investigate how to generate innovative work behaviors among Millennial and Generation Z sport employees and its impact on their career satisfaction and psychological well-being.

The authors used structural equation modeling to examine the relationships among predictors of job engagement, innovative work behaviors, career satisfaction and psychological well-being. The model was tested across managerial sport employees of Division I athletics departments (N = 224).

The highlights of the study include job engagement's positive relationship with innovative work behaviors and the positive influence of innovative work behavior on career satisfaction and psychological well-being.

These findings signify the importance of considering job engagement and innovative work behaviors to develop a positive work experience for Millennial and Generation Z sport employees. Doing so is thought to be a critical step in cultivating an organizational competitive advantage via younger generations of sport employees.

To develop electrode materials for supercapacitor with superior electrochemical performance and simple preparation process, the purpose of this study is to prepare flexible CC/NiS/a-NiS electrodes with self-supporting structure by loading hydrothermally synthesized a-NiS particles along with nano-NiS on carbon cloth by electroplating method.

The effects of current densities, temperatures and pH values on the loading amount and uniformity of the active substances during the plating process were investigated on the basis of optimization of surface morphology, crystalline structure and electrochemical evaluation as the cyclic voltammetry curves, constant current charge–discharge curves and AC impedance.

The a-NiS particles on CC/NiS/a-NiS were mostly covered by the plated nano-NiS, which behaved as a bulge and provided a larger specific surface area. The CC/NiS/a-NiS electrode prepared with the optimized parameter exhibited a specific capacitance of 115.13 F/g at a current density of 1 A/g and a Coulomb efficiency of 84% at 5 A/g, which is superior to that of CC/NiS electrode prepared by electroplating at a current density of 10 mA/cm², a temperature of 55°C and a pH of 4, demonstrating its fast charge response of the electrode and potential application in wearable electronics.

This study provides an integrated solution for the development of specifically structured NiS-based electrode for supercapacitor with simple process, low cost and high electrochemical charge/discharge performance, and the simple and easy-to-use method is also applicable to other electrochemically active composites.

With the increasing number of Web services, correct and efficient classification of Web services is crucial to improve the efficiency of service discovery. However, existing Web service classification approaches ignore the class overlap in Web services, resulting in poor accuracy of classification in practice. This paper aims to provide an approach to address this issue.

This paper proposes a label confusion and priori correction-based Web service classification approach. First, functional semantic representations of Web services descriptions are obtained based on BERT. Then, the ability of the model is enhanced to recognize and classify overlapping instances by using label confusion learning techniques; Finally, the predictive results are corrected based on the label prior distribution to further improve service classification effectiveness.

Experiments based on the ProgrammableWeb data set show that the proposed model demonstrates 4.3%, 3.2% and 1% improvement in Macro-F1 value compared to the ServeNet-BERT, BERT-DPCNN and CARL-NET, respectively.

This paper proposes a Web service classification approach for the overlapping categories of Web services and improve the accuracy of Web services classification.

With big data (BD), traditional supply chain is shifting to digital supply chain. This study aims to address the issues and challenges in the way toward the implementation of big data analytics (BDA) in sustainable supply chain management (SSCM).

The factors that affect the implementation of BDA in SSCM are identified through a widespread literature review. The PESTEL framework is used for this purpose as it covers all the political, economic, social, technological, environmental and legal factors. These factors are then finalized by means of experts' opinion and analyzed using structural equation modeling (SEM).

A total of 10 factors are finalized with 31 sub-factors, of which sustainable performance, competitive advantage, stakeholders' involvement and capabilities, lean and green practices and improvement in environmental performance are found to be the critical factors for the implementation of BDA in SSCM.

This research has taken up the case of Indian manufacturing industry. It can be diversified to other geographical areas and industry sectors. Further, the quantitative analysis may be undertaken with structured or semi-structured interviews for validation of the proposed model.

This research provides an insight to managers regarding the implementation of BDA in SSCM by identifying and examining the influencing factors. The results may be useful for managers for the implementation of BDA and budget allocation for BDA project.

The result includes green practices and environmental performance as critical factors for the implementation of BDA in SSCM. Thus the research establishes a positive relationship between BDA and sustainable manufacturing that ultimately benefits the environment and society.

This research addresses the challenges in the implementation of BDA in SSCM in Indian manufacturing sector, where such application is at its nascent stage. The use of PESTEL framework for identifying and categorizing the factors makes the study more worthwhile, as it covers full spectrum of the various factors that affect the strategic business decisions.

Cyberloafing is an organization-directed counterproductive work behavior (CWB). One stream of literature deems cyberloafing to be bad for organizations and their employees, while another suggests cyberloafing is a coping response to stressful work events. Our work contributes to the latter stream of literature. The key objective of our study is to examine whether cyberloafing could be a means to cope with a stressful work event-abusive supervision, and if yes, what mediating and boundary conditions are involved. For this investigation, the authors leveraged the Stressor-Emotion-CWB theory which posits that individuals engage in CWB to cope with the negative affect generated by the stressors and that this relationship is moderated at the first stage by personality traits.

Using a multi-wave survey design, the authors collected data from 357 employees working in an Indian IT firm. Results revealed support for three out of the four hypotheses.

Based on the Stressor-Emotion-CWB theory, the authors found that work-related negative affect fully mediated the positive relationship between abusive supervision and cyberloafing, and work locus of control (WLOC) moderated the positive relationship between abusive supervision and work-related negative affect. The authors did not find any evidence of a direct relationship between abusive supervision and cyberloafing. Also, the positive indirect relationship between abusive supervision and cyberloafing through work-related negative affect was moderated at the first stage by the WLOC such that the indirect effect was stronger (weaker) at high (low) levels of WLOC.

This work demonstrates that cyberloafing could be a way for employees to cope with their abusive supervisors.

This study aims to examine the moderating effect of sustainability marketing on brand loyalty of brands that advertise their sustainable development agenda goals. The study highlights the mediating effect of brand love having cognitive antecedents of brand authenticity, popularity and congruence with private and social self of the consumer.

A mall intercept survey was used to collect data from consumers who use brands that embrace sustainable marketing strategies. Only those brands were selected which are popular as well as advertise sustainable practices in their brand communication (mainstream and social media). The data was self-administered by trained research assistants, who gathered data from a sample of 350 respondents.

The findings revealed that the popularity and authenticity of a brand play an essential role in developing brand love and later influences brand loyalty behavior. A larger effect is seen on brand love when there is congruence of private and social self with the brand. The brand has even a stronger relationship with brand loyalty when moderated by sustainability marketing.

Brand love has the potential for long-term influences, only if sustainability marketing is used as a backbone. Brand managers should target an authenticity-seeking segment of consumers, who once convinced can lead to repeat business and brand loyalty and reduce dissonance. As sustainability marketing provides multiple benefits, genuine branding strategies should be devised that amalgamate into a single message spun around sustainability concerns and connecting the ethos of authenticity, popularity and self-expression. Future research may take into consideration more categories than this study on clothing, and consumer goods, adopting a mixed-methods approach. Moreover, a range of potential antecedents of brand love can be determined along with potential outcomes when aligned with external efforts such as sustainability, corporate social responsibility and international investment.

To the best of the authors’ knowledge, this is the first study investigating the moderating role of sustainability marketing on the relationship between brand love and brand loyalty and the mediating role of brand love between brand authenticity, popularity, social/private-self-expression and brand loyalty. It is also the first study documenting how sustainability marketing reinforces the brand loyalty for popular brands in developing countries like Pakistan. This study fills a research gap as it expands the existing literature on sustainability marketing and brand love that is generally focused on brand dimensions and not the brand communications and thus has not reached similar results.

Sports marketing and sponsorship research is located at the intersection of behavioral and design research, which means that it analyzes the current world and shapes a future world. This dual focus poses challenges for formulating and testing theories of sports marketing.

This article develops criteria for categorizing theoretical concepts as either behavioral or formed as different ways of expressing ideas of sports marketing research. It emphasizes the need for clear concept categorization for proper operationalization and applies these criteria to selected theoretical concepts of sports marketing and sponsorship research.

The study defines three criteria to categorize theoretical concepts, namely (1) the guiding idea of research, (2) the role of observed variables, and (3) the relationship among observed variables. Applying these criteria to concepts of sports marketing research manifests the relevance of categorizing theoretical concepts as either behavioral or formed to operationalize concepts correctly.

This study is the first in sports marketing to clearly categorize theoretical concepts as either behavioral or formed, and to formulate guidelines on how to differentiate behavioral concepts from formed concepts.