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In academics and industry, significant efforts have been made to lead planners and control teams in evaluating project performance and control. In this context, numerous control metrics have been devised and put into practice, often with little emphasis on analyzing their underlying concepts. To cover this gap, this research aims to identify and analyze a holistic list of control metrics and their functionalities in the construction industry.

A multi-step analytical approach was conducted to achieve the study’s objectives. First, a holistic list of control metrics and their functionalities in the construction industry was identified. Second, a quantitative analysis based on social network analysis (SNA) was implemented to discover the most important functionalities.

The results revealed that the most important control metrics' functionalities (CMF) could differ depending on the type of metrics (lagging and leading) and levels of control. However, in general, the most significant functionalities include managing project progress and performance, evaluating the look-ahead level’s performance, measuring the reliability and stability of workflow, measuring the make-ready process, constraint management and measuring the quality of construction flow.

This research will assist the project team in getting a comprehensive sensemaking of planning and control systems and their functionalities to plan and control different dynamic aspects of the project.

This study addresses how algorithmic recommendations and their affordances shape everyday information practices among young people.

Thematic interviews were conducted with 20 Finnish young people aged 15–16 years. The material was analysed using qualitative content analysis, with a focus on everyday information practices involving online platforms.

The key finding of the study is that the current affordances of algorithmic recommendations enable users to engage in more passive practices instead of active search and evaluation practices. Two major themes emerged from the analysis: enabling not searching, inviting high trust, which highlights the how the affordances of algorithmic recommendations enable the delegation of search to a recommender system and, at the same time, invite trust in the system, and constraining finding, discouraging diversity, which focuses on the constraining degree of affordances and breakdowns associated with algorithmic recommendations.

This study contributes new knowledge regarding the ways in which algorithmic recommendations shape the information practices in young people's everyday lives specifically addressing the constraining nature of affordances.

A positive outlook on the impact of Industry 4.0 (I4.0) on sustainability prevails in the literature. However, some studies have highlighted potential areas of concern that have not yet been systematically addressed. The goal of this study is to challenge the assumption of a sustainable Fourth Industrial Revolution by (1) identifying the possible unintended negative impacts of I4.0 technologies on sustainability; (2) highlighting the underlying motivations and potential actions to mitigate such impacts; and (3) developing and evaluating alternative assumptions on the impacts of I4.0 technologies on sustainability.

Building on a problematization approach, a systematic literature review was conducted to develop potential alternative assumptions about the negative impacts of I4.0 on sustainability. Then, a Delphi study was carried out with 43 experts from academia and practice to evaluate the alternative assumptions. Two rounds of data collection were performed until reaching the convergence or stability of the responses.

The results highlight various unintended negative effects on environmental and social aspects that challenge the literature. The reasons behind the high/low probability of occurrence, the severity of each impact in the next five years and corrective actions are also identified. Unintended negative environmental effects are less controversial than social effects and are therefore more likely to generate widely accepted theoretical propositions. Finally, the alternative hypothesis ground is partially accepted by the panel, indicating that the problematization process has effectively opened up new perspectives for analysis.

This study is one of the few to systematically problematize the assumptions of the I4.0 and sustainability literature, generating research propositions that reveal several avenues for future research.

This paper aims to help higher education institutions (HEIs) develop a better understanding of student support and services needs, thereby enabling them to allocate limited resources for initiatives that effectively improve student experience.

An assessment framework following the Kano analysis is developed to categorize student service features based on customer satisfaction and need fulfillment. The framework is used at a local university, using 23 service features listed as minimum requirements by the national regulatory body for education. Analysis of the satisfaction survey results and prioritization are based on quality indices derived from a factor of importance and the satisfaction gap. A survey was conducted for two academic years to generate a comparison of results.

Of the list mandated as minimum requirements for HEIs, the study revealed that no features were regarded as “must-be,” eight as performing, 14 as attractive and one as indifferent by the students. As these results were disaggregated per year level, the natural decay of delight as in the Kano theory was exhibited as there were less attractive features for students who have been in the university longest. After a full-year academic cycle, results compared to the baseline figures seemed to reveal of impact of the achievement of performance targets by the units rendering specific activities on client satisfaction.

Further rounds of the study are needed to build up more data sets on the relationship between objective performance and satisfaction level for performing features, mindful that this categorization is also bound to change along the way.

As HEIs in the Philippines journey towards the establishment of their own respective internal quality assurance systems, this study provides a practical approach for institutions to transform a mere list of student services for compliance into a strategic tool to enhance the student experience.

In the context of continuous quality improvement, the study presents how the qualitative Kano model, along with simple quantitative tools in the methodology, can be utilized not only in the planning stage of service design but also in closing the planning, doing, checking and acting (PDCA) cycle and opening the quality improvement spiral.

This study aims to elucidate institutional analysis as an effective approach to investigating and designing the multilevel policymaking system of online social networks (OSN) for achieving a participatory model.

The institutional mapping approach has been used to analyze Iran’s OSN multilevel policymaking system. A combination of two matrices, including institutions-institutions and institutions-functions, was used to perform the institutional mapping. Two main steps were taken to draw the mentioned matrices. First, a review of related studies in Iran’s OSN policymaking system was conducted and the policy functions mentioned in these studies were identified and categorized using the meta-synthesis. Second, based on analyzing two policy documents of Iran’s OSN, institutions and their interactions were identified and policy functions were allocated to institutions.

Based on the results, the most important policy functions in the current OSN policymaking system in Iran are support, regulatory, monitoring and evaluation, business environment development, culture building and promotion, organizing licenses and permissions, policymaking and legislation. Also, the results show that there are shortcomings in this system, some of the most important of which are lack of transparency in regulatory, little work in culture building and promotion, neglect of the training of specialized human resources and research and development, slow development of the business environment and neglecting the role of nongovernmental organizations in policymaking.

By examining and analyzing how different institutions operate within a multilevel policymaking system, the policymaking process and its overall effectiveness can be enhanced. This analysis helps identify any inconsistencies, overlaps or conflicts in the roles and policies of these institutions, leading to a better understanding of how a multilevel policymaking system is organized.

The study aims to explore and validate the revised psychological contract scale in this new normal era.

To serve the purpose, four studies were conducted. Study 1 was conducted for item generation through the extant literature review and phenomenological study. Study 2 highlighted the expert review. Study 3 explained the confirmatory factor analysis. At the end of study 3, the new psychological contract content had 14 items along with 15 traditional psychological contract content items. The nomological study validated the scale with the help of antecedent, i.e. supervisor's support, and outcomes, i.e. well-being and innovative behavior.

The revised psychological contract was bifurcated into two categories: new and traditional. Further, the revised psychological contract scale was having two dimensions: content and breach/fulfillment. The new content was the outcome of changes in perceived obligations due to pandemic. The nomological study found that supervisor support had a positive impact on the content of the psychological contract and fulfillment/breach of the psychological contract. Further, it was found that the new content of psychological contract was impacting more on well-being and innovative behavior than the traditional psychological contract.

In the new normal era, the working style and patterns have changed. Thus, it was important to capture changes in perceived obligations and employees' perception regarding to which extent their organizations were able to meet these altered perceived obligations. The study has direct implications for the practitioners as the revised psychological contract scale enlisted the perceived obligations of the employee and the extent to which these obligations were fulfilled by the employer. The study is also helpful in developing new normal HR policies and practices in the organization.

The study is original as it creates a new scale to measure the content of psychological contract and fulfillment/breach of psychological contract during new normal.

The main purpose of this paper is to explore whether the nature of innovation is accumulative or radical and to what extent past year accumulation of technology stock can predict future innovation. More importantly, the authors are concerned with whether a change of policy regime or a variance in the quality of technology will moderate the nature of innovation.

The authors examined a dataset of 3.6 million Chinese patents during 1985–2015 and constructed more than 5 million citation pairs across 8 sections and 128 classes to track knowledge spillover across technology fields. The authors used this citation dataset to calculate the technology innovation network. The authors constructed a measure of upstream invention, interacting the pre-existing technology innovation network with historical patent growth in each technology field, and estimated measure's impact on future innovation since 2005. The authors also constructed three sets of metrics – technology dependence, centrality and scientific value – to identify innovation quality and a policy dummy to consider the impact of policy on innovation.

Innovation growth is built upon past year accumulation and technology spillover. Innovation grows faster for technologies that are more central and grows more slowly for more valuable technologies. A pro-innovation and pro-intellectual property right (IPR) policy plays a positive and significant role in driving technical progress. The authors also found that for technologies that have faster access to new information or larger power to control knowledge flow, the upstream and downstream innovation linkage is stronger. However, this linkage is weaker for technologies that are more novel or general. On most occasions, the nature of innovation was less responsive to policy shock.

This paper contributes to the debate on the nature of innovation by determining whether upstream innovation has strong predictive power on future innovation. The authors develop the assumption used in the technology spillover literature by considering a time-variant, directional and asymmetric matrix to model technology diffusion. For the first time, the authors answer how the nature of innovation will vary depending on the technology network configurations and policy environment. In addition to contributing to the academic debate, the authors' study has important implications for economic growth and industrial or innovation management policies.