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Video summarisation is one of the most active fields in content‐based video retrieval research. A new video summarisation scheme is proposed by this paper based on socially generated temporal tags.

To capture users' collaborative tagging activities the proposed scheme maintains video bookmarks, which contain some temporal or positional information about videos, such as relative time codes or byte offsets. For each video all the video bookmarks collected from users are then statistically analysed in order to extract some meaningful key frames (the video equivalent of keywords), which collectively constitute the summary of the video.

Compared with traditional video summarisation methods that use low‐level audio‐visual features, the proposed method is based on users' high‐level collaborative activities, and thus can produce semantically more important summaries than existing methods.

It is assumed that the video frames around the bookmarks inserted by users are informative and representative, and therefore can be used as good sources for summarising videos.

Folksonomy, commonly called collaborative tagging, is a Web 2.0 method for users to freely annotate shared information resources with keywords. It has mostly been used for collaboratively tagging photos (Flickr), web site bookmarks (Del.icio.us), or blog posts (Technorati), but has never been applied to the field of automatic video summarisation. It is believed that this is the first attempt to utilise users' high‐level collaborative tagging activities, instead of low‐level audio‐visual features, for video summarisation.

The idea of implementing supply chain management (SCM) principles for the construction industry was embraced by construction stakeholders to enhance the sector's performance. The analysis from the literature revealed that the implementation of SCM in the construction industry enhances the industry's value in terms of cost-saving, time savings, material management, risk management and others. The construction supply chain (CSC) can be managed using the pull or push system. This chapter also discusses the origin and proliferation of SCM into the construction industry. The chapter revealed that the concept of SCM has passed through five different eras: the creation era, the use of ERP, globalisation stage, specialisation stage and electronic stage. The findings from the literature revealed that we are presently in the fourth industrial revolution (4IR) era. At this stage, the SCM witnesses the adoption of technologies and principles driven by the 4IR. This chapter also revealed that the practice of SCM in the construction industry is centred around integration, collaboration, communication and the structure of the supply chain (SC). The forms and challenges hindering the adoption of these practices were also discussed extensively in this chapter.

The purpose of this paper is to address the gap between definition and practical aspects of production efficiency in mass customization (MC). The paper summarizes all major issues impacting efficiency in MC. Also, the paper reviews metrics, relationship between various parameters and provides a best practices benchmark toolkit to achieve higher machine efficiencies.

The paper identified and categorized multiple challenges impacting machine efficiency in MC through a literature review spanning over three decades, and also ranked the identified issue-based parameters. Top issues were found varying across different types of industries identified through the review. Metrics pertaining to efficiency and degree of MC are reviewed in the paper. A chronological review of issues is presented, and a chain diagram is built in the paper. Toolkit of best practices created with solution strategies and tools are summarized through the review.

The paper found that MC reasonably impacts machine efficiency which needs to be addressed. Major issues through literature review-based ranking are uncovered, and worldwide research trend and comparison are presented. Active research in this area is observed to be at its peak since 2010. The extensive use of strategies and benchmark toolkit for improving efficiency are summarized.

Ranking of issues has been done through a literature review; hence, there can be skewness depending on the frequency of issues researched by various authors in various areas of industries.

This paper is useful for manufacturing managers and companies willing to increase the size of their product portfolio and choices within their available resources without compromising machine efficiencies and, thereby, the cost. The identified issues help in providing a comprehensive issue list to the academia.

This paper describes what is believed to be the first study that explicitly examines the issues faced in achieving machine efficiency while manufacturing in an MC environment.

This research blends perspectives of the Eastern phenomenon of guanxi with the more Western perspectives of relationship marketing and customer centricity. Extending scholarship on guanxi in marketing (e.g. Park and Luo, 2001; Sheu and Hu, 2009; Luo et al., 2008; Fowler and Reisenwitz, 2014), the objective is to highlight the indirect role of customer centricity (i.e. how visible or central it is for the business partner to communicate with/have information sharing with), for firms in regions with a prevalence of guanxi.

The empirical model is tested in context of global marketing in the business-to-business (B2B) logistics industry (n = 508). A total of 508 global logistics employees and managers with experience in global business participated in the survey in Taiwan. Structural equation modeling was used for data analysis with multi-group analyses.

Customer centricity intensifies positive outcomes of guanxi prevalence. Specifically, a high level of customer centricity strengthens established associations among guanxi prevalence, trust, relationship commitment and firm performance.

While most work on guanxi has a focus in China, this research focuses on Taiwan. While building on a wealth of literature, relatively less work has focused on customer centricity.

The time series analysis is an essential methodology which comprises the tools for analyzing the time series data to identify the meaningful characteristics for making future ad-judgments. The purpose of this paper is to propose a Taylor series approximation and unbiased GM(1,1) based new hybrid statistical approach (HTS_UGM(1,1)) for forecasting time series data under the poor, incomplete and uncertain information systems in a short period of time manner.

The gray forecasting is a dynamical methodology which can be classified into different categories based on their respective functions. The new proposed methodology is made up of three different methodologies including the first-order unbiased GM(1,1), Markov chain and Taylor approximation. In addition to that, two different traditional gray operational mechanisms include GM(1,1) and unbiased GM(1,1) used as the comparisons. The main objective of this study is to forecast gold price demands in a short-term manner based on the data which were taken from the Central Bank of Sri Lanka from October 2017 to December 2017.

The error analysis results suggested that the new proposed HTS_UGM(1,1) is highly accurate (less than 10 percent) with lowest RMSE error values in a one head as well as weakly forecasting’s than separate gray forecasting methodologies.

The findings suggested that the new proposed hybrid approach is more suitable and effective way for forecasting time series indices than separate time series forecasting methodologies in a short-term manner.

Making decisions in finance have been regarded as one of the biggest challenges in the modern economy today; especially, analysing and forecasting unstable data patterns with limited sample observations under the numerous economic policies and reforms. The purpose of this paper is to propose suitable forecasting approach based on grey methods in short-term predictions.

High volatile fluctuations with instability patterns are the common phenomenon in the Colombo Stock Exchange (CSE), Sri Lanka. As a subset of the literature, very few studies have been focused to find the short-term forecastings in CSE. So, the current study mainly attempted to understand the trends and suitable forecasting model in order to predict the future behaviours in CSE during the period from October 2014 to March 2015. As a result of non-stationary behavioural patterns over the period of time, the grey operational models namely GM(1,1), GM(2,1), grey Verhulst and non-linear grey Bernoulli model were used as a comparison purpose.

The results disclosed that, grey prediction models generate smaller forecasting errors than traditional time series approach for limited data forecastings.

Finally, the authors strongly believed that, it could be better to use the improved grey hybrid methodology algorithms in real world model approaches.

However, for the large sample of data forecasting under the normality assumptions, the traditional time series methodologies are more suitable than grey methodologies; especially GM(1,1) give some dramatically unsuccessful results than auto regressive intergrated moving average in model pre-post stage.

The purpose of this paper is to develop a professional self-efficacy scale for counsellors and psychologists encompassing identified competencies within professional standards from national and related international frameworks for psychologists and counsellors.

An initial opportune sample of postgraduate psychology and counselling students (n=199) completed a ten-minute self-report survey. A subsequent independent sample (n=213) was recruited for cross-validation.

A series of exploratory analyses, consolidated through confirmatory factor analyses and Rasch analysis, identified a well-functioning scale composed of 31 items and five factors (research, ethics, legal matters, assessment and measurement, intervention).

The Psychologist and Counsellor Self-Efficacy Scale (PCES) appears a promising measure, with potential applications for reflective learning and practice, clinical supervision and professional development, and research studies involving psychologists’ and counsellors’ self-perceived competencies. It is unique in being ecologically grounded in national competency frameworks, and extending previous work on self-efficacy for particular competencies to the set of specified attributes outlined in Australian national competency documents. The PCES has potential utility in a variety of applications, including research about training efficacy and clinical supervision, and could be used as one component of a multi-method approach to formative and summative competence assessment for psychologists and counsellors. The scale may be used to assess students’ perceived competencies relative to actual competency growth against national standards, and to identify trainees’ and practitioners’ self-perceived knowledge deficits and target areas for additional training.