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The purpose of the study was to benchmark meta-analytical conceptualizations of business-to-business (B2B) seller skills against empirical evidence in services firms.

The study is based on a deductive approach and questionnaire survey focusing on a range of services firms from different industries and corporate sizes. A total of 389 questionnaires out of 732 were returned, generating a response rate of 53.1%.

The study aims to provide empirical evidence and structures relating to B2B sellers' capabilities in a seven-dimensional conceptualization, all of which can be used in services firms to improve their seller efficiency. Each seller skill dimension performs a different function in the sales services process.

The authors conclude that the verified meta-analytical conceptualizations of B2B seller skills seem valid and reliable in services firms. Nevertheless, further research needs to be carried out, based on other company characteristics as well as industries.

It reduces the risk perceived by customers in B2B services settings through cultivating the sellers' capabilities, based on the seven-dimensional evidence of seller skills to enhance sales performance.

The study contributes to existing theory and previous studies by offering a foundation on which to structure sales performance indicators in services firms. Specifically, it contributes to structuring B2B seller skills across a selection of principal dimensions in B2B services settings.

Warranty-based big data analysis has attracted a great deal of attention because of its key capabilities and role in improving product quality while minimizing costs. Information and details about particular parts (components) repair and replacement during the warranty term, usually stored in the after-sales service database, can be used to solve problems in a variety of sectors. Due to the small number of studies related to the complete analysis of parts failure patterns in the automotive industry in the literature, this paper focuses on discovering and assessing the impact of lesser-studied factors on the failure of auto parts in the warranty period from the after-sales data of an automotive manufacturer.

The interconnected method used in this study for analyzing failure patterns is formed by combining association rules (AR) mining and Bayesian networks (BNs).

This research utilized AR analysis to extract valuable information from warranty data, exploring the relationship between component failure, time and location. Additionally, BNs were employed to investigate other potential factors influencing component failure, which could not be identified using Association Rules alone. This approach provided a more comprehensive evaluation of the data and valuable insights for decision-making in relevant industries.

This study's findings are believed to be practical in achieving a better dissection and providing a comprehensive package that can be utilized to increase component quality and overcome cross-sectional solutions. The integration of these methods allowed for a wider exploration of potential factors influencing component failure, enhancing the validity and depth of the research findings.

Many buildings fail to meet user expectations, causing a performance gap. Pre-occupancy evaluation (PrOE) is believed to have the potential to close the gap. It enables designers to obtain end-user feedback in the design phase and improve the design for better performance. However, PrOE implementation faces challenges due to still maturing knowledgebase. This study aims to understand the state-of-the-art knowledge of PrOE, thereby identifying future research needs to advance the domain.

A systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) framework was conducted. A thorough search in five databases and Google Scholar retrieved 90 articles, with 30 selected for systematic review after eliminating duplicates and irrelevant articles. Bibliometric analyses were performed using VOSviewer and Biblioshiny on the article metadata, and thematic analyses were conducted on their contents.

PrOE is a vehicle for engaging building end-users in the design phase to address the credibility gap caused by the discrepancies between the expected and actual performance of buildings. PrOE has gained limited applications in healthcare, residential, office and educational building design for two broad purposes: design management and marketing. Using virtual reality technologies for PrOE has demonstrated significant benefits. Yet, the PrOE domain needs to mature in multiple perspectives to serve its intended purpose effectively.

This study identifies four knowledge gaps for future research to advance the PrOE domain: (1) developing a holistic PrOE framework, integrating comprehensive performance evaluation criteria, useable at different stages of the design phase and multi-criteria decision algorithms, (2) developing a mixed reality tool, embodying the holistic PrOE framework, (3) formulating a PrOE framework for adaptive reuse of buildings and (4) managing uncertainties in user requirements during the lifecycle in PrOE decisions.

The purpose of this study is to provide an in-depth understanding of the B2B customers’ perspective regarding salespeople’s social media use.

The study adopts a qualitative approach based on semi-structured interviews with 26 key informants performing their job in customer role in various industries.

The authors inductively identify five themes regarding the B2B customers’ perspective of social media use in B2B selling. These themes allow for valuable implications for social selling activities and expected outcomes.

Against a growing body of literature on drivers, best practices and outcomes of social media use by B2B salespeople, less attention has been paid to the customer’s side. The authors extend current research by providing a more complete picture of social selling activities and expected outcomes.

Heritage buildings are a witness to previous civilizations and constitute important elements in transmitting cultural identity through generations. In 1938, Alexandria University was established; it was called the University of Farouk at the time. In 1952, the university was named “Alexandria University,” and since then, it has witnessed growth and expansion in several fields. The research aims to preserve the heritage of this academic institution. It seeks to document this wealth of buildings that tell the story of the second-earliest university in Egypt.

A mixed-method approach was employed. A descriptive method was used to narrate the history of the university and the importance of its buildings. Within the quantitative approach, a questionnaire was chosen as the survey instrument for collecting the data within the research case study. The aim was to determine the awareness of students, staff and employees of the heritage importance of their faculty. Within the qualitative approach, several interviews were conducted with employees in the engineering departments of the university administrative building at Chatby and some of the selected faculties. The aim was to determine the methods used for the conservation of these buildings.

Alexandria University has a heritage value not only in its great history but also through its heritage buildings. Raising the awarness of the university's affiliates of this heritage will lead to enhance the feelings of loyalty and belongings to the university. Therefore, preserving this heritage and properly managing it is crucial.

Universities have to recognize that their built heritage constitutes a unique expression that can create a distinctive sense of place. University heritage is crucial in defining and interpreting the university cultural identity. The institution must identify resources that will help build a new public image and contribute to develop a successful brand. Campus appearance is an important factor that has a significant impact on student feelings of loyalty and belonging.

Attention deficit hyperactivity disorder (ADHD) is a neuro-developmental condition that has frequently been pathologised in career research and broader society to date. The study seeks to reframe such assumptions through a qualitative positive-focused exploration of career stories of ADHD adults, elicited through a strength-focused technique with wide applicability for coaching and other career-based development activities.

Situated in a strength-focused coaching psychology paradigm, the authors undertook semi-structured interviews with 17 participants, using an adapted feedforward interview technique (FFI) rooted in positive psychology (PP), to investigate individuals' strengths and successful career experiences.

Narrative thematic analysis of the transcripts identified two core themes: “the paradoxical nature of strengths” and “career success as an evolving narrative”. The participants described how they have achieved career success both “in spite of” and “because of” ADHD. The use of the FFI demonstrated a helpful and easily taught method for eliciting personal narratives of success and strengths, an essential foundation to any coaching process.

This research provides a nuanced overview, and an associated conceptual model, of how adults with ADHD perceive their career-based strengths and experiences of success. Further, the research shows the value of using a positive psychological coaching approach when working with neurominority individuals, using a successful adaptation of the FFI. The authors hope that the documentation of this technique and the resulting insights will offer important guidance for managers as coaches and internal and external career coaches, as well as providing positive and relatable narrative resources for ADHD adults.

This paper aims to apply several data mining techniques for predicting the daily precision improvement of Jakarta Islamic Index (JKII) prices based on big data of symmetric volatility in Indonesia’s Islamic stock market.

This research uses big data mining techniques to predict daily precision improvement of JKII prices by applying the AdaBoost, K-nearest neighbor, random forest and artificial neural networks. This research uses big data with symmetric volatility as inputs in the predicting model, whereas the closing prices of JKII were used as the target outputs of daily precision improvement. For choosing the optimal prediction performance according to the criteria of the lowest prediction errors, this research uses four metrics of mean absolute error, mean squared error, root mean squared error and R-squared.

The experimental results determine that the optimal technique for predicting the daily precision improvement of the JKII prices in Indonesia’s Islamic stock market is the AdaBoost technique, which generates the optimal predicting performance with the lowest prediction errors, and provides the optimum knowledge from the big data of symmetric volatility in Indonesia’s Islamic stock market. In addition, the random forest technique is also considered another robust technique in predicting the daily precision improvement of the JKII prices as it delivers closer values to the optimal performance of the AdaBoost technique.

This research is filling the literature gap of the absence of using big data mining techniques in the prediction process of Islamic stock markets by delivering new operational techniques for predicting the daily stock precision improvement. Also, it helps investors to manage the optimal portfolios and to decrease the risk of trading in global Islamic stock markets based on using big data mining of symmetric volatility.

This research is a pioneer in using big data mining of symmetric volatility in the prediction of an Islamic stock market index.

The purpose of this study is to identify the main perspectives and trends in educational data mining (EDM) in the e-learning environment from a managerial perspective.

This paper proposes a systematic literature review to identify the main perspectives and trends in EDM in the e-learning environment from a managerial perspective. The study domain of this review is restricted by the educational concepts of e-learning and management. The search for bibliographic material considered articles published in journals and papers published in conferences from 1994 to 2023, totaling 30 years of research in EDM.

From this review, it was observed that managers have been concerned about the effectiveness of the platform used by students as it contains the entire learning process and all the interactions performed, which enable the generation of information. From the data collected on these platforms, there are improvements and inferences that can be made about the actions of educators and human tutors (or automatic tutoring systems), curricular optimization or changes related to course content, proposal of evaluation criteria and also increase the understanding of different learning styles.

This review was conducted from the perspective of the manager, who is responsible for the direction of an institution of higher education, to assist the administration in creating strategies for the use of data mining to improve the learning process. To the best of the authors’ knowledge, this review is original because other contributions do not focus on the manager.

The purpose of this study is to understand the investment decision-making of real estate investors in housing, highlighting the interplay between rational and irrational factors. In this study, investment satisfaction was a mediator, while reinvestment intention was the dependent variable.

A quantitative, cross-sectional and descriptive research design was used, gathering data from a sample of 550 residential real estate investors using a multi-stage stratified sampling technique. The partial least squares structural equation modelling disjoint two-stage approach was used for data analysis. This methodological approach allowed for an in-depth examination of the relationship between rational factors such as location, profitability, financial viability, environmental considerations and legal aspects alongside irrational factors including various biases like overconfidence, availability, anchoring, representative and information cascade.

This study strongly supports the adaptive market hypothesis, showing that residential real estate investor behaviour is dynamic, combining rational and irrational elements influenced by evolutionary psychology. This challenges traditional views of investment decision-making. It also establishes that behavioural biases, key to adapting to market changes, are crucial in shaping residential property market efficiency. Essentially, the study uncovers an evolving real estate investment landscape driven by evolutionary behavioural patterns.

This research redefines rationality in behavioural finance by illustrating psychological biases as adaptive tools within the residential property market, urging a holistic integration of these insights into real estate investment theories.

The study reshapes property valuation models by blending economic and psychological perspectives, enhancing investor understanding and market efficiency. These interdisciplinary insights offer a blueprint for improved regulatory policies, investor education and targeted real estate marketing, fundamentally transforming the sector’s dynamics.

Unlike previous studies, the research uniquely integrates human cognitive behaviour theories from psychology and business studies, specifically in the context of residential property investment. This interdisciplinary approach offers a more nuanced understanding of investor behaviour.

The study explores the relationship between the breadth of external pressures facing leaders of small and medium-sized enterprises (SMEs) and the entrepreneurial stance they adopt for their firm, that is, entrepreneurial orientation (EO).

Blending attention theory with EO literature, we argue that increasing breadth of external pressures will challenge leaders' attentions with implications for how they seek innovation, risk-taking and bold acts. We highlight an inflection point after which a negative relationship between the breadth of external pressure and EO will turn positive. We use data from a survey of 125 small-sized wineries in France to test this and capture a range of 15 external pressures on entrepreneurs.

The main tests and additional robustness tests provide support. It is the breadth of external pressures – as opposed to intensity of any one specific form of pressure – that plays a fundamental role in shaping leaders' adoption of EO in small enterprises over and above internal characteristics.

While the results may be context-dependent, they provide support for an attention-based view of entrepreneurial responses by leaders of SMEs under pressure.

SME leaders and entrepreneurs should be aware of how their attention is challenged by breadth of pressures from external sources, as this can influence the EO they adopt for their SME.

This nonlinear perspective on external pressures influencing the EO of small firms has not been taken in the EO literature to date, despite some recent work that considers only a small range of external pressures.