Ricardo Jose Chacon Vega, Stephen P. Gale, Yujin Kim, Sungil Hong and Eunhwa Yang
This study aims to investigate the performance of open-plan office layouts and to identify occupants’ concerns in existing open-plan office layouts.
Abstract
Purpose
This study aims to investigate the performance of open-plan office layouts and to identify occupants’ concerns in existing open-plan office layouts.
Design/methodology/approach
Workplace activity questionnaire (WAQ) was administered in the form of an online survey in March 2019, as part of a design briefing process for the expansion of the office facilities located in Bangalore, India, for a Fortune 100 software technology company. A total of 4,810 questionnaires were distributed and 3,877 responses were received (80.6% response rate). After that, 849 incomplete responses were eliminated from the analysis, resulting in a final sample size of 3,028. The questionnaire included 11 key activities conducted by the office workers and established the gap between the workers’ perceived importance and support from their existing facilities using a five-point Likert scale.
Findings
The findings of this study provide strong evidence that different physical environments influence the satisfaction of occupants. An improvement of the facilities, especially by enabling areas for quiet working, should be prioritized in relation to the other activities surveyed. Also, office workers perceived significantly different support levels for quiet working depending on their department, while there was no significant difference between the workers of different buildings.
Research limitations/implications
Individual demographic information was not collected because of the possibility of personal identification. There was also a lack of objective environmental measures, such as temperature and noise level. Thus, the quality of indoor environments was unknown. In this study, some respondents mentioned dissatisfaction with indoor environmental quality, including noise, temperature and air quality in their comments.
Originality/value
In the programming stage of a workplace design process, the WAQ survey tool has value because it renders important insight into the perception of a live workplace, which can then be used to determine priorities for a design effort. It clearly identifies the areas to focus on, ask questions about and develop improvements. Validating its reliability will enhance its credibility and confidence in its use. In addition, the large sample size provides statistical advantages in the data analysis, providing a higher likelihood to find a true positive of the findings of the study. Also, having a relatively high response rate provides an advantage of mitigating the risk of having non-response bias in the analysis.
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Eunhwa Yang, Yujin Kim and Sungil Hong
This study aims to understand how knowledge workers working from home during COVID-19 changed their views on physical work environments and working-from-home practices.
Abstract
Purpose
This study aims to understand how knowledge workers working from home during COVID-19 changed their views on physical work environments and working-from-home practices.
Design/methodology/approach
This study conducted a survey targeting workers in the USA recruited via Amazon Mechanical Turk. A total of 1,651 responses were collected and 648 responses were used for the analysis.
Findings
The perceived work-life balance improved during the pandemic compared to before, while the balance of physical boundaries between the workplace and home decreased. Workplace flexibility, environmental conditions of home offices and organizational supports are positively associated with productivity, satisfaction with working from home and work-life balance during the pandemic.
Research limitations/implications
While the strict traditional view of “showing” up in the office from Monday through Friday is likely on the decline, the hybrid workplace with flexibility can be introduced as some activities are not significantly affected by the work location, either at home-based or corporate offices. The results of this study also highlight the importance of organizations to support productivity and satisfaction in the corporate office as well as home. With the industry collaboration, future research of relatively large sample sizes and study sites, investigating workers’ needs and adapted patterns of use in home-based and corporate offices, will help corporate real estate managers make decisions and provide some level of standardization of spatial efficiency and configurations of corporate offices as well as essential supports for home offices.
Originality/value
The pandemic-enforced working-from-home practices awaken the interdependence between corporate and home environments, how works are done and consequently, the role of the physical workplace. This study built a more in-depth understanding of how workers who were able to continue working from home during COVID-19 changed or not changed their views on physical work environments and working-from-home practices.
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Sungil Hong, Yujin Kim and Eunhwa Yang
This study investigates the relationships between the built environments of learning commons and user productivity, such as collaborative and individual work productivity and…
Abstract
Purpose
This study investigates the relationships between the built environments of learning commons and user productivity, such as collaborative and individual work productivity and overall environmental satisfaction.
Design/methodology/approach
A case study was conducted in a learning commons building at a higher education campus in the USA. The data collection and analysis were conducted with the survey responses of satisfaction with indoor environments and perceived productivity as well as the objective indoor environmental quality (IEQ) measurements. Statistical analysis was performed, including descriptive analysis, principal component analysis (PCA), regression analysis and ANOVA test.
Findings
The study presents that satisfaction with noise level is positively associated with individual productivity. The results imply that the spatial properties of open-plan commons, such as visibility and accessibility, are associated with space users' interactions and collaborative productivity. Overall satisfaction is in a positive relationship with lighting satisfaction, study supporting artifacts and furniture configuration. The results of this study reveal the importance of meeting the standards in IEQ factors on individual productivity and the spatial features preferred by space users that facilitate tasks and activities.
Originality/value
The mixed-method approach, including subjective and objective data collection of IEQ, is rarely utilized to show the relationships with perceived productivity. This study investigates a unique building design feature such as step seats in relation to space use and perceived productivity. The findings inform library leadership about environmental characteristics related to the user experience in learning commons, a new format of academic libraries.
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Sungil Lee and Shijin Yoo
The purpose of this paper is twofold – the first is to explore the key actions that enabled Pizza Hut Korea (PHK) to come out of a nine‐year decline in sales and profits. The…
Abstract
Purpose
The purpose of this paper is twofold – the first is to explore the key actions that enabled Pizza Hut Korea (PHK) to come out of a nine‐year decline in sales and profits. The second purpose is to delve deeper into the concept of return on marketing as applied to the turnaround of Pizza Hut Korea, using customer lifetime value (LTV) and the related return on marketing investment (ROMI) principles that were instrumental in turning around the business.
Design/methodology/approach
The main method used is interviews with company senior management, reviews of internal company data as well as external data and literature reviews of existing theories on return on marketing. The case uses a specific promotional decision that senior management must make to review the decision methodologies using return on marketing. This quantified return estimate is then combined with marketing and business strategic considerations to review the decision that management should make regarding the promotion. In addition, the detailed executive interviews shed light on the approaches taken by the senior management to effect a change in culture as well as the disciplined business reviews that were put in place to improve the financial performance. Finally the case describes the marketing insights that led the firm to implement their consumer promotions to help turn the business around.
Findings
Turning around a business that has been in decline for a long time requires not just keen consumer insight and excellent marketing tactics, it is a combination of changing the culture of the company and mindset of the leaders along with instilling disciplined financial processes and driving consumer insight driven strategies. In particular, this study focuses on the role of quantified marketing investment return model that helped to drive a fact‐based, data‐driven decision‐making process that, combined with strategic insight, helped to turn the business around. The lifetime value and return on marketing investment model employed by Pizza Hut Korea provides a starting framework for analyzing marketing investment returns that can be adapted by many other companies.
Originality/value
Though there has been research conducted in many turnaround situations, there has been virtually no work done to examine the turnaround strategies employed using key marketing return metrics. In addition, the study provides value in that it examines the totality of management principles employed (cultural, organizational, financial, marketing) to drive innovation and change. This study will be useful for those that seek to better understand the key principles involved in turning around a business but with particular emphasis on quantified marketing returns analysis using return on marketing investment method.
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Medhat Abd el Azem El Sayed Rostum, Hassan Mohamed Mahmoud Moustafa, Ibrahim El Sayed Ziedan and Amr Ahmed Zamel
The current challenge for forecasting smart meters electricity consumption lies in the uncertainty and volatility of load profiles. Moreover, forecasting the electricity…
Abstract
Purpose
The current challenge for forecasting smart meters electricity consumption lies in the uncertainty and volatility of load profiles. Moreover, forecasting the electricity consumption for all the meters requires an enormous amount of time. Most papers tend to avoid such complexity by forecasting the electricity consumption at an aggregated level. This paper aims to forecast the electricity consumption for all smart meters at an individual level. This paper, for the first time, takes into account the computational time for training and forecasting the electricity consumption of all the meters.
Design/methodology/approach
A novel hybrid autoregressive-statistical equations idea model with the help of clustering and whale optimization algorithm (ARSEI-WOA) is proposed in this paper to forecast the electricity consumption of all the meters with best performance in terms of computational time and prediction accuracy.
Findings
The proposed model was tested using realistic Irish smart meters energy data and its performance was compared with nine regression methods including: autoregressive integrated moving average, partial least squares regression, conditional inference tree, M5 rule-based model, k-nearest neighbor, multilayer perceptron, RandomForest, RPART and support vector regression. Results have proved that ARSEI-WOA is an efficient model that is able to achieve an accurate prediction with low computational time.
Originality/value
This paper presents a new hybrid ARSEI model to perform smart meters load forecasting at an individual level instead of an aggregated one. With the help of clustering technique, similar meters are grouped into a few clusters from which reduce the computational time of the training and forecasting process. In addition, WOA improves the prediction accuracy of each meter by finding an optimal factor between the average electricity consumption values of each cluster and the electricity consumption values for each one of its meters.