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This paper presents the phenomenographic analysis of students' approaches to learning in the first year architectural design coursework; thereby correlating contextualization in the architectural curriculum.

This paper reviews phenomenographic data of first year architecture students' learning experience through a comparative analysis of first- and fourth-year students' approaches to learning in the design studio; further co-relating this analysis to the final classification involving all five years of students' learning approaches in the architecture program.

Five meta-categories of the comparative analysis and nineteen meta-categories of the final classification are evaluated using first-year students' learning approaches – to understand the importance of contextualization in curriculums of architecture.

This phenomenographic analysis of first-year students' learning experience represents the onward journey from surface-to-deep approaches to learning that is encountered in their learning approaches, pertaining to the design process in the design coursework during five years of architectural education.

This paper systematically extends the discussion of first year architecture students' engagement in the design process that leads to deep learning; further delving into the static dimension of knowledge and its extension to the dynamic dimension of knowing architecture.

Study on knowledge-based systems for scientific publications is growing very broadly. However, most of these studies do not explicitly discuss the knowledge management (KM) component as knowledge management system (KMS) implementation. This background causes academic institutions to face challenges in developing KMS to support scholarly publication cycle (SPC). Therefore, this study aims to develop a new KMS conceptual model, Identify critical components and provide research gap opportunities for future KM studies on SPC.

This study used a systematic literature review (SLR) method with the procedure from Kitchenham et al. Then, the SLR results are compiled into a conceptual model design based on a framework on KM foundations and KM solutions. Finally, the model design was validated through interviews with related field experts.

The KMS for SPC focuses on the discovery, sharing and application of knowledge. The majority of KMS use recommendation systems technology with content-based filtering and collaborative filtering personalization approaches. The characteristics data used in KMS for SPC are structured and unstructured. Metadata and article abstracts are considered sufficiently representative of the entire article content to be used as a search tool and can provide recommendations. The KMS model for SPC has layers of KM infrastructure, processes, systems, strategies, outputs and outcomes.

This study has limitations in discussing tacit knowledge. In contrast, tacit knowledge for SPC is essential for scientific publication performance. The tacit knowledge includes experience in searching, writing, submitting, publishing and disseminating scientific publications. Tacit knowledge plays a vital role in the development of knowledge sharing system (KSS) and KCS. Therefore, KSS and KCS for SPC are still very challenging to be researched in the future. KMS opportunities that might be developed further are lessons learned databases and interactive forums that capture tacit knowledge about SPC. Future work potential could identify other types of KMS in academia and focus more on SPC.

This study proposes a novel comprehensive KMS model to support scientific publication performance. This model has a critical path as a KMS implementation solution for SPC. This model proposes and recommends appropriate components for SPC requirements (KM processes, technology, methods/techniques and data). This study also proposes novel research gaps as KMS research opportunities for SPC in the future.

To address the absence of Lean in transportation logistics in the digital era, this study aims to investigate the application of Lean transportation (LT) tools to reduce waste and facilitate the digital transformation of dedicated road transportation in the offshore industry.

The study adopts action research with a multimethod approach, including a scoping review, focus groups (FG) and participant observation. The research is conducted within the offshore supply chain of a major oil and gas company.

Implementing LT’s continuous improvement tools, particularly value stream mapping (VSM), reduces offshore transportation waste and provides empirical evidence about the intersection of Lean and digital technologies. Applying techniques drawn from organisational learning theory (OLT), stakeholders involved in VSM mapping and FGs engage in problem-solving and develop action plans, driving digital transformation. Waste reduction in loading and unloading stages leads to control actions, automation and process improvements, significantly reducing downtime. This results in an annual monetary gain of US$1.3m. The study also identifies waste related to human effort and underutilised digital resources.

This study contributes to theory and practice by using action research and LT techniques in a real intervention case. From the lens of OLT, it highlights the potential of LT tools for digital transformation and demonstrates the convergence of waste reduction through Lean and Industry 4.0 technologies in the offshore supply chain. Practical outputs, including a benchmarking questionnaire and a plan-do-check-act cycle, are provided for other companies in the same industry segment.

The ageing and disabled population is fast growing, which emphasises the need to effectively modify current homes and environments to support healthy ageing and increasingly diverse health needs. This paper aims to bring together findings and analyses from three adaptations-focussed projects, drawing on perspectives from key stakeholders alongside the lived experiences of service users acquiring adaptations.

Following an Adaptations Framework developed from interviews and focus groups with older people and key stakeholders, the paper discusses barriers experienced by older people and front-line workers in receiving and delivering adaptations through all stages of the process.

This paper reveals how experiences around adaptations might diverge with unseen, hidden investment and need amongst individuals, and how conceptual and cost-focussed evidence gaps impact wider understandings of adaptations delivery. In so doing, this paper highlights how the adaptations process is perceived as a “fight” that does not work smoothly for either those delivering or receiving adaptations services.

The paper suggests a systematic failure such that the adaptations process needs to be rehauled, reset and prioritised within social and public policy if the housing, health and social care sectors are to support healthy ageing and prepare for the future ageing population.

The paper brings together insights from key stakeholders alongside service users' experiences of adaptations to highlight key policy drivers and barriers to accessing and delivering adaptations.

This study aims to identify the impact of intellectual capital (IC) on the bank’s performance using a cross-country approach with India and Gulf Cooperation Council (GCC) countries using the Skandia navigator model (SNM).

This study uses a mixed-methods research approach by taking financial and non-financial measures to assess the impact of the IC on the bank’s performance using the SNM. The study implies an analysis of the data from the top ten banks in India and twenty banks in GCC countries. The selection was done based on the volume of the bank’s business for three years (2019–2020, 2020–2021 and 2021–2022).

The research has three main findings: there is a positive impact of IC on the bank’s performance; amongst the factors of SNM, there is a direct impact of human capital and customer focus on the performance of the selected banks in both India and GCC countries; and the other factors of SNM such as structural capital and process focus, renewal and development focus also affect the selected banks.

The outcomes of the research may be useful for policymakers in India and GCC countries, as it identifies IC components that have a significant impact on the bank’s performance. This might enable them to develop policies that foster such factors, which, consequently, will improve the performance of the banks in the selected countries.

This study is an attempt to fill the gap in the existing literature on IC and bank’s performance for two different types of countries using the SNM.

The purpose of this study is to identify the factors that contribute to the successful implementation and management of sustainable innovation in research-intensive sectors such as the life sciences industry.

The study was conducted through a combination of two methods. The first was qualitative interviews of 21 sustainability experts and leaders in the life sciences industry who were responsible for implementing sustainable innovation. They were selected through nonprobabilistic purposive sampling. The second method was thematic content analysis using the MAXQDA software.

The study identified that successful implementation of sustainable innovation in research-intensive firms begins with the alignment of the executive vision for sustainability with the business objectives of the research-intensive firm. Furthermore, implementation of sustainability practices is identified as a function of organizational reconfigurations that facilitate purposeful inflow and outflow of ideas and knowledge between internal firm resources and external stakeholders, anchored by the objectives of the research-intensive firm.

The study explicated factors only within life sciences industry based on qualitative interviews. The study offers scope for cross-sector quantitative evaluation.

To the best of the authors’ knowledge, this study is among the first studies to systematically delineate the underlying factors that govern successful implementation of sustainable innovation in research-intensive industries, through integration of the resource-based view and stakeholder theory and thereby provide a framework for research-intensive organizations to implement sustainable innovation practices.

The purpose of this paper is to investigate and measure stakeholder engagement and interorganisational relationships involved in the project design process.

A mixed-methods design, which combined action study, focus group meetings and a survey with project stakeholders who were employees in this project to express their comments on current design processes in different sub-projects.

The transformation of the design process in the selected project can be categorised into three distinct areas: (1) people, (2) practices and (3) internal infrastructure. These three categories were a straightforward way to review, analyse and discuss this transformation. The findings revealed the major goals of the improvement process as summarised are reliability, efficiency and quality. Recommendations and future study directions were suggested by the end of the paper.

Although the project selected in this research was limited to Australia, the results could be interpreted on the design process in many other construction projects with similar size all over the world.

This research was very practical, with all data collected from the project in Australia. It summarised the difficulties met in the project and provided methods for stakeholders and industry practitioners to improve the effectiveness and efficiency of the design process.

This research provided lessons learnt on the design process from a “Giga” project and provided sustainable methods to facilitate future projects into flexible and effective communication among stakeholders.

The current research aims to analyze the literature to determine its strengths and weaknesses and extract the required information, which will be used to identify the characteristics of the highly competitive organization (HCO), define it and identify the HCO's critical success factors (CSFs). Finally, the future research agenda will be proposed.

A multiple stages research methodology was used to fulfill the research objectives. The research started with the systematic literature review (SLR). Then, focus group discussions and Pareto analysis were used to fulfill research objectives.

Eleven points were identified in the research to represent the characteristics of the HCO. Then, the HCO was defined based on the elements of these points. Moreover, the vital few CSFs to successfully implement many research scopes were identified. Then, the CSFs of the HCO was generated based on these vital few CSFs.

The main limitation of the current research is the literature sample size. A larger sample selection could enrich the generated lists with many other CSFs.

Many implications points were highlighted in this research which showed the importance of the current research for academic and practical audiences.

The SLR process showed that the reviewed literature lacked a consolidated list of the HCO characteristics and a clear definition of the HCO. Moreover, the reviewed literature lacked a unified list of the HCO CSFs. Therefore, the current research approach is novel and original.

The purpose of this paper is to provide an overview of what (service) experience is and examine it using three distinct perspectives: customer experience (CX), employee experience (EX) and human experience (HX).

The present conceptualization blends the marketing and organizational behavior/human resources management (OB/HRM) disciplines to clarify and reflect over the meaning of (service) experience. The marketing discipline illuminates the concept of CX, whereas the OB/HRM discipline illuminates the concept of EX. The concept of HX, which transcends CX and EX, is examined in light of its recent development in service research. For each of the three concepts, key themes are identified, and future research directions are proposed.

Because the goal that individuals seek to achieve depends on the role they are enacting, each of the three perspectives on experience (CX, EX and HX) should have a different focal point. CX requires to focus on the process of solving customer goals. EX necessitates to think in terms of organizational context and job content that support employees. Finally, the focus of HX should be on well-being via enhanced gratification, and reduced violation, of basic human needs.

This paper offers an interdisciplinary perspective on (service) experience and simultaneously addresses CX, EX and HX in order to reconcile the different perspectives on experience in service research.

As the number of web applications is increasing day by day web mining acts as an important tool to extract useful information from weblogs and analyse them according to the attributes and predict the usage of a website. The main aim of this paper is to inspect how process mining can be used to predict the web usability of hotel booking sites based on the number of users on each page, and the time of stay of each user. Through this paper, the authors analyse the web usability of a website through process mining by finding the web usability metrics. This work proposes an approach to finding the usage of a website using the attributes available in the weblog which predicts the actual footfall on a website.

PROM (Process Mining tool) is used for the analysis of the event log of a hotel booking site. In this work, authors have used a case study to apply the PROM (process mining tool) to pre-process the event log dataset for analysis to discover better-structured process maps than without pre-processing.

This article first provided an overview of process mining, then focused on web mining and later discussed process mining techniques. It also described different target languages: system nets (i.e. Petri nets with an initial and a final state), inductive miner and heuristic miner, graphs showing the change in behaviour of the dataset and predicting the outcome, that is the webpage having the maximum number of hits.

In this work, a case study has been used to apply the PROM (process mining tool) to pre-process the event log dataset for analysis to discover better-structured process maps than without pre-processing.