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This study investigates the impact of social media marketing activities on customer purchase intention in the Malaysian property market.

The study utilises a survey research approach to collect data from 331 respondents using a questionnaire.

The findings of the study reveal that entertainment, interaction, customisation and word-of-mouth variables had a significant and positive impact on customer purchase intention in the Malaysian property market. However, the study demonstrates a positive but insignificant impact of trendiness on customer purchase intention.

First, the study relies on a sample of 331 respondents in Malaysia, which may limit the generalizability of the findings to a broader population. Hence, future research could aim for a more extensive and diverse sample to enhance the validity of the results. Second, while the study identified significant relationships, the measurement of variables, in particular “trendiness,” could be refined for better accuracy. The future study may consider including a more precise measurement to provide comprehensive insights.

The results suggest that marketers should focus on creating engaging and interactive content, providing personalised experiences and leveraging word-of-mouth recommendations to enhance customer purchase intention. The overall findings highlight the importance of social media marketing activities in the property market and their potential to drive customer purchase intention.

The study contributes to the existing literature by shedding light on the role of social media marketing activities in influencing customer purchase intention in the Malaysian property market.

To the best of the authors’ knowledge, there is no similar studies have been conducted in this area of research.

The model and existing practice of the construction supply chain (CSC) in the United Kingdom (UK) and Australia was presented in this chapter. The policies and reports that support the practice of the CSC were examined in both countries. It was discovered from the review of literature that the UK has a more detailed report targeted at improving the CSC than Australia. However, both countries have a common factor affecting their CSC which originates from fragmentation experienced within their supply chain. Construction stakeholders in the UK and Australia believe that collaboration and integration are vital components for improving performance. The majority of the contractors in both countries embrace collaborative working for the sole purpose of risk sharing, access to innovation and response to market efficiency. However, most of the models developed for managing the CSC in the UK are built around building information modelling (BIM). Also, the reviewed studies show that supply chain management practice will be effective following the following principle: shared objectives, trust, reduction in a blame culture, joint working, enhanced communication and information-sharing. Finally, the UK has a more established framework and more CSC models compared to Australia.

This research uses accounting information to supplement abnormal returns evidence in order to gauge the performance of greenmailed firms. Our results support the management entrenchment hypothesis; target firm earnings are poor relative to industry in the years surrounding the greenmail event, and earnings do not significantly improve as would be expected under the shareholders' interest hypothesis. This result holds after adjusting for greenmail premia net of tax effects. Evidence on investment spending suggests firms that pay greenmail differ substantially from their industries, but in a negative direction. In contrast, the industry‐adjusted earnings of non‐greenmail repurchasing firms are significantly greater than the earnings of greenmailed firms. Together, these results are consistent with the contention that greenmailed firms are not managed in shareholders' interests; they underperform their industry, the poor operating results are not attributable to higher investment outlays associated with a long‐term strategic focus, and performance does not improve. This is consistent with observed negative abnormal returns being attributable to both a lost takeover premium and a lost opportunity for improved corporate performance.

This study aims to assess the feasibility and effectiveness of incorporating predictive maintenance (PdM) into existing practices of spare part inventory management and pinpoint the barriers and identify economic values for such integration within the supply chain (SC).

A two-staged embedded multiple case study with multi-method data collection and a combined discrete/continuous simulation were conducted to diagnose obstacles and recommend a potential solution.

Several major organisational, infrastructure and cultural obstacles were revealed, and an optimum scenario for the integration of spare part inventory management with PdM was recommended.

The proposed solution can significantly decrease the inventory and SC costs as well as machinery downtimes through minimising unplanned maintenance and addressing shortage of spare parts.

This is the first study with the best of our knowledge that offers further insights for practitioners in the Industry 4.0 (I4.0) era looking into embarking on digital integration of PdM and spare part inventory management as an efficient and resilient SC practice for the automotive sector by providing empirical evidence.

This research aims to evaluate the factors that influence logistics outsourcing, including the impact of logistics outsourcing on measuring companies' logistics performance. This research provides interactions among the various factors (constructs) such as “financial”, “collaboration and process characteristics”, “external influencer”, and “logistics performance”.

To investigate the interaction between the constructs, structural equation modelling is proposed to understand what the relevant criteria are while outsourcing logistics. Data were acquired from surveys conducted with 129 managers from Brazilian companies in the industry sector.

The factor “collaboration and process characteristics” is what most influences the “logistics performance” of companies, highlighting the importance of managing contractors; and the “financial” factor also contributes to the logistic outsourcing decision.

Some limitations of this study need to be clarified. First, the model could test the moderate and mediate aspects by using variables inspired on RBV and TCE. Second, the sample is relatively small and restricted to the Brazilian industries' case, although the results may be useful for other countries in the world. Third, the responses represent viewpoints of the people who work in the companies. To address this issue, the authors asked respondents to fill out the questionnaire from the perspective of the organisation.

Most 3PL come from developed countries and find different requirements in Brazil. Then, this new knowledge may help 3L providers better understand the needs of the local or foreign companies that operate in the local market. The measurement model may also help to construct a new organisational process, as it sheds light on the main elements necessary for gathering logistics performance outcomes.

To the best of the authors' knowledge, the literature lacks studies on the interaction among these logistics outsourcing constructs, mainly in emerging markets where significant growth opportunities have led to logistics activities being outsourced. The literature that examines the impact of these constructs on logistics performance is also limited. Therefore, this research contributes to providing a model that measures these impacts according to the company's point of view.

Looks at the distinctive Australian background and the features of the national communication culture that may impact on business life as well as those of the traditional executive culture. Brings out the specifics of the Australian management style from a foreign viewpoint, looking at what differences exist compared to New Zealand, the United States and Asian countries. Concludes that Australians need to develop understanding of the global market whilst retaining their easy regard in which they are held.

This paper presents a review of the existing state-of-the-art literature on machine learning (ML) in logistics and supply chain management (LSCM) by analyzing the current literature, contemporary concepts, data and gaps and suggesting potential topics for future research.

A systematic/structured literature review in the subject discipline and a bibliometric analysis were organized. Information regarding industry involvement, geographic location, research design and methods, data analysis techniques, university, affiliation, publishers, authors, year of publications is documented. A wide collection of eight databases from 1994 to 2019 were explored using the keywords “Machine Learning” and “Logistics“, “Transportation” and “Supply Chain” in the title and/or abstract. A total of 110 articles were found, and information on a chain of variables was gathered.

Over the last few decades, the application of emerging technologies has attracted significant interest all around the world. Analysis of the collected data shows that only nine literature reviews have been published in this area. Further, key findings show that 53.8 per cent of publications were closely clustered on transportation and manufacturing industries and 54.7 per cent were centred on mathematical models and simulations. Neural network is applied in 22 papers as their exclusive algorithms. Finally, the main focuses of the current literature are on prediction and optimization, where detection is contributed by only seven articles.

This review is limited to examining only academic sources available from Scopus, Elsevier, Web of Science, Emerald, JSTOR, SAGE, Springer, Taylor and Francis and Wiley which contain the words “Machine Learning” and “Logistics“, “Transportation” and “Supply Chain” in the title and/or abstract.

This paper provides a systematic insight into research trends in ML in both logistics and the supply chain.

The purpose of this paper is to empirically investigate the corporate image as a high-order construct in the hospitality industry. Therefore, it includes an important part of all the agents that contribute to the formation of this corporate image: the clients, the employees and the hotel management.

In order to better conceptualize and understand the dimensions of corporate image in the hospitality industry, a theoretical systematization and analysis of the literature on corporate image definitions and validated scales to date are presented. The primary research is based on a questionnaire survey that emerged from the theoretical model. The collected data were tested using confirmatory factor analysis and covariance-based structural equation modelling (CB-SEM).

Results indicate that corporate image is a high-order construct that includes the dimensions of symbols from servicescape, employees' behaviour, perception of the organization, perception of the management, perception of the service and perception of the hotel.

The application of this paper will enable new research in the corporate marketing literature, while the presented multidimensional approach will support future empirical research on corporate image in hospitality.

The paper contributes to theory by conceptualizing the corporate image as high-order construct. It provides evidence of corporate image multidimensionality, comprising six dimensions. Moreover, the findings provide an insight for practitioners to better understand how to manage hotel image.

The purpose of this paper is twofold: first, to develop a performance evaluation framework for construction and demolition waste management (CDWM); second, to investigate feasible and effective strategies to improve the CDWM performance.

A review of the literature highlighted a lack of comprehensive research to evaluate CDWM performance of key project stakeholders, like owners, contractors and consultants. After the identification of 22 performance variables through a pilot study, a first questionnaire survey was conducted to investigate the views of respondents toward CDWM performance. The 132 responses were analyzed using factor analysis to determine specific CDWM performance factors, which formed a conceptual performance evaluation framework of CDWM. Furthermore, a practical index (PI) was proposed to integrate the feasibility and effectiveness of CDWM strategies. The values of PI were employed to prioritize CDWM strategies from data collected in a second questionnaire survey.

The validated results from factor analysis revealed that the conceptual performance evaluation framework of CDWM consists of six factors; and the attitude toward CDWM emerged as the foremost critical factor. The prioritization of PI values indicated that raising CDWM awareness among construction stakeholders was the most feasible and effective strategy for CDWM.

This CDWM performance evaluation framework is one of the first to holistically evaluate CDWM from key stakeholder perspectives. In addition, the PI firstly enables quantitative integration of the feasibility and effectiveness of CDWM strategies.

This study considers transitive service triads, which consist of three dyads formed by three actors: supplier, logistics service provider and customer, who remain directly linked by one or more of the upstream and downstream flows of products, information and finances. This paper aims to explore the link between information governance, decentralized information technologies and supply chain self-organization, and their resulting impact on network performance in the transitive service triads.

Drawing upon the tenets of the theory of complex adaptive systems and supply chain practice view, this paper involves an empirical investigation that uses survey data gathered from transitive service triads in the European countries. The study uses partial least squares structural equation modeling to estimate the formative-reflective hierarchical component model and test the research hypotheses.

Information governance defines how supply chain information flows are controlled, accessed and used by a focal organization and its business partners. As empirically evidenced in this study, it can be depicted as a latent construct consisting of three distinct dimensions of information custody, information ownership and right to data access. Likewise, the study also indicates that supply chain self-organization, as a second-order construct, consists of three interactive self-organization actions undertaken by specific firms participating in the triadic arrangement. Supply chain self-organization is thus produced by firms that are reciprocally interrelated and interacting, having effects on one another. Furthermore, the study also highlights that information governance creates an environment for applying decentralized information technologies, which then positively affects supply chain self-organization. Finally, the research also empirically operationalizes the construct of network performance within the transitive service triads.

Although the results provide several major contributions to theory and implications for practitioners, the study still demonstrates some methodological constraints. Specifically, although the study uses a relatively large research sample of 350 transitive service triads, it still focuses only on a selected group of industries and is limited to investigating solely a particular type of service triads.

Given the increasing interest in investigating triads, this study examines how information governance and decentralized information technologies support supply chain self-organization to yield network performance in transitive service triads.