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Dealing with Desirable Inputs in Data Envelopment Analysis: A Slacks-based Measure Approach
Issue:
Volume 6, Issue 4, December 2021
Pages:
67-74
Received:
6 October 2021
Accepted:
21 October 2021
Published:
30 October 2021
Abstract: In Data Envelopment Analysis (DEA) the situation of inputs vs. outputs is positioned as cause and effect. Effects include desirable (ordinary) outputs and undesirable outputs, e.g. pollutants. This situation is well studied and many applications have been published. In this paper, we introduce a new type of inputs, called Good (Desirable) Inputs. As explained in Introduction, we find several examples of such inputs, e.g. Electric car, Women in office and Test takers of vaccine. We handle this by means of SBM (Slacks-based Measure). Usually, efficiency values of DEA models are in the range (0, 1], while in this model a negative efficiency value may be assigned to inefficient DMUs (decision making units). This is caused by shortages of Good Input values. As an example, we refer to “Women’s Rights Movements” in a country where women’s right is not fully guaranteed. Suppose local governments where men and women are serving as officers. They are inputs to office, while Women are Desirable input and Men are Ordinary input. As outputs, we assume Service as Ordinary output and Claim as Undesirable output. Several extensions of this model are introduced. (a) Variable returns to scale, (b) Weight restrictions, (c) Super-efficiency issue and (d) SBM_Max model.
Abstract: In Data Envelopment Analysis (DEA) the situation of inputs vs. outputs is positioned as cause and effect. Effects include desirable (ordinary) outputs and undesirable outputs, e.g. pollutants. This situation is well studied and many applications have been published. In this paper, we introduce a new type of inputs, called Good (Desirable) Inputs. A...
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Requirements Analysis and Design of IRB System
Joshua Nwokeji,
Walter Iwanenko
Issue:
Volume 6, Issue 4, December 2021
Pages:
75-85
Received:
24 July 2021
Accepted:
9 November 2021
Published:
24 December 2021
Abstract: Institutional review boards (IRB) are established by institutions to protect (human) research subjects from abuse. Researchers are thus required to apply and obtain IRB ap- proval for any research initiative that involves human subjects. Currently, most USA institutions use paper-based or partially automated approaches for IRB application, review, and approval processes. This can be cumbersome, error-prone and usually add unnecessary workloads to researchers. Moreover, paper- based approaches can delay or reduce research output, especially during collaborative research projects if researchers are from different institutions. Web-based information systems can be developed and used to streamline IRB application and approval processes. Before such web-based systems can be developed, the requirements of the system have to be analyzed and designed. However, requirements analysis and design are usually very tedious and expensive project, which may discourage some institutions from implementing systems to support IRB processes. The aim of this paper is to contribute a set of requirements and systems models that can be customized and re-used, by other institutions, to develop IRB Systems. Accordingly, we provide the following models, use case, feature tree model, and network diagram. In addition, we discussed our experiences and systems analysis principles we adopt to make this project a success. We believe that the experiences we share and the models we provide in this paper can inform practice and advance the knowledge of web-based information systems development. Re-using existing requirements and designs can also help to reduce the amount of time and cost required to develop similar systems.
Abstract: Institutional review boards (IRB) are established by institutions to protect (human) research subjects from abuse. Researchers are thus required to apply and obtain IRB ap- proval for any research initiative that involves human subjects. Currently, most USA institutions use paper-based or partially automated approaches for IRB application, review, ...
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The Pricing of Meetings and Event Spaces in Hotel Revenue Management
Issue:
Volume 6, Issue 4, December 2021
Pages:
86-91
Received:
26 November 2021
Accepted:
15 December 2021
Published:
24 December 2021
Abstract: In this paper, we discuss the pricing of Meetings and Event Spaces in Hotel Revenue Management. We use a measure called Attendee Density, for a Meeting and Event Space, which is similar to the measure of Occupancy for a hotel room. Based on the method for forecasting Occupancy for a hotel room, we forecast Attendee Density for an Event Space. The Attendee Density is the ratio of Attendees Booked to Capacity. To forecast Attendee Density, we have to forecast how many attendees will book in the future. To forecast how many attendees will book at a specific date in the future, we sum our current Reservations on Hand and a quantity called the Pickup. The Pickup is calculated based on a Booking Curve. The Booking Curve is a graph which plots Reservations on Hand against Time. It shows us how bookings happen leading upto a particular event. Once we calculate Pickup based on the Booking Curve, we can forecast how many attendees will book at a date in the future. We can then calculate Attendee Density. A high Attendee Density for the future results in charging a High Price today. On the other hand, a low future Attendee Density results in charging a Low Price currently. We also discuss how we can go about determining a High Price and a Low Price for a Meeting and Event Space.
Abstract: In this paper, we discuss the pricing of Meetings and Event Spaces in Hotel Revenue Management. We use a measure called Attendee Density, for a Meeting and Event Space, which is similar to the measure of Occupancy for a hotel room. Based on the method for forecasting Occupancy for a hotel room, we forecast Attendee Density for an Event Space. The A...
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Effect of Internal Branding on Employees’ Brand Supporting Behaviors: Empirical Evidence from the Higher Education Institutions of Ethiopia
Issue:
Volume 6, Issue 4, December 2021
Pages:
92-101
Received:
19 November 2021
Accepted:
14 December 2021
Published:
24 December 2021
Abstract: Nowadays, companies are increasing their brand value by cooperating and committing to a consistent brand message in order for employees to understand the value embodied in the brand and brings the brand promise to their customers. The purpose of this study is to investigate the effect of internal branding activities on the brand support behavior of employees at Welega University. The researcher used internal brand communication and brand-centered training and development activities as a feature of internal branding. This study followed a descriptive study design supported by a deductive study approach. The subjects of the survey consisted of all employees of the University. A dedicated, unlikely sampling procedure was used to track the last respondent. Data were collected from 346 respondents using a structured survey using a 5-point Likert scale. The findings of the association analysis show that the descriptive variables were statistically significant. The results of root cause analysis show that internal branding attributes, or the practice of internal brand communication, have a greater impact on the brand support behavior of university employees than on brand-centric training and further development activities. In addition, the results show that internal branding attributes are positively correlated with employee brand support behavior and that the university has excellent experience with these attributes, employees are very likely to support the brand.
Abstract: Nowadays, companies are increasing their brand value by cooperating and committing to a consistent brand message in order for employees to understand the value embodied in the brand and brings the brand promise to their customers. The purpose of this study is to investigate the effect of internal branding activities on the brand support behavior of...
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