A Management Support System for Directing and Monitoring the Activities of University Academic Staff

1994 ◽  
Vol 45 (6) ◽  
pp. 641
Author(s):  
Paul N. Finlay ◽  
Geoffrey Gregory
Keyword(s):  
Support System ◽  
Academic Staff ◽  
Management Support

EFFECT OF TOP MANAGEMENT SUPPORT, SYSTEM QUALITY, AND INFORMATION QUALITY ON SATISFACTION ACCOUNTING INFORMATION SYSTEM USERS IN LEMBAGA PERKREDITAN DESA (LPD) IN UBUD DISTRICT

2019 ◽  
Vol 1 (1) ◽  
pp. 123-142
Author(s):  
Sang Ayu Putu Arie Indraswarawati ◽  
I Putu Deddy Samtika Putra ◽  
Ni Wayan Cahyani
Keyword(s):  
Information System ◽  
Support System ◽  
User Satisfaction ◽  
Information Quality ◽  
Accounting Information ◽  
Top Management ◽  
Management Support ◽  
System Quality ◽  
Accounting Information System ◽  
Top Management Support

The use of Accounting Information System (AIS) is very helpful in accommodating all the information needed to make an accurate decision. Indicators in determining the good and bad performance of an information system can be seen through AIS user satisfaction and usage. The purpose of this study was to determine the effect of top management support, system quality and information quality on AIS user satisfaction. The sample selection method used was purposive sampling. The research sample was 147 people consisting of administrators, loan officers and savings at 29 Lembaga Perkreditan Desa (LPD) in Ubud Subdistrict. The data in this study is primary data which is the answer from the questionnaire. The regression results show that all variables have a significance of 0,000. It shows that top management support, system quality and information quality have positive influences on Accounting Information System user satisfaction.

Pengembangan Sistem Penunjang Operasional dan Pengelolaan Sumber Daya Manusia untuk Laboratorium Komputer

2015 ◽  
Vol 6 (1) ◽  
pp. 12-19
Author(s):  
Angellia Debora Suryawan ◽  
Marlene Martani ◽  
Mahenda Metta Surya
Keyword(s):  
Resource Management ◽  
Human Resources ◽  
Human Resource Management ◽  
Human Resource ◽  
Support System ◽  
Performance Indicator ◽  
Management Support ◽  
Key Performance Indicator ◽  
Literature Study ◽  
Operational Support System

Human resources are an important asset in the entire company operations activity. A human resources management support system should be provided to improve performance in  accordance with the company target. The purpose of this study is to design a model of operational and human resource management support systems that can integrate employee performance data, simplify management of employee data, and generate reports in the form of Key Performance Indicator (KPI) and Binusian Level. Methodology used in this study is using literature study, design, and test a model to make operational and human resource management information system. Index Terms - human resources, operational support system, Key Performance Indicator (KPI)  

ABC Inventory Management Support System With a Clinical Laboratory Application

2012 ◽  
Vol 18 (4) ◽  
pp. 414-435 ◽  
Author(s):  
Hooshang M. Beheshti ◽  
Dale Grgurich ◽  
Faye W. Gilbert
Keyword(s):  
Inventory Management ◽  
Support System ◽  
Clinical Laboratory ◽  
Management Support

scholarly journals Role of Perceived Management Support and Personal Valence in Promoting Behavioral Support for Change: A Social Exchange Theory Perspective

2020 ◽  
Vol 5 (1) ◽  
pp. 65-74
Author(s):  
Farhan Mehboob ◽  
Noraini Othman
Keyword(s):  
Social Exchange ◽  
Positive Impact ◽  
Academic Staff ◽  
Success Factor ◽  
Management Support ◽  
Behavioral Support ◽  
Cross Sectional ◽  
Context Factor ◽  
Behavioural Support

Individuals’ support for change is a critical success factor to effectively implement change. Therefore, identifying the possible antecedent and mechanism leading to one’s behavioural support towards change is necessary. The study aims to unfold this avenue of research empirically by examining the role of both person and context factor in promoting behavioral support for change. Data was collected from 292 academic staff of six public sector universities in Pakistan via cross-sectional mean. A self-reported questionnaire was used to collect responses from the desired sample. SPSS 25 and AMOS were used to analyse the data for its relevance to study’s objectives. Results revealed a positive impact of perceived management support on academic staff’s behavioural support for change. Moreover, personal-valence provides an effective intervening mechanism to translate the effect of perceived management support on both dimensions of behavioural support for change such as compliance and championing behaviour. The study contributes to the existing literature on organizational change particularly to the university settings by examining and empirically validating both person and context factor as significant predictors to academic staff’s behavioral support for change.

The Evaluation of Decision-Making Support Systems' Functionality

2011 ◽  
pp. 329-338 ◽  
Author(s):  
Giusseppi Forgionne ◽  
Stephen Russell
Keyword(s):  
Decision Making ◽  
Support System ◽  
Support Systems ◽  
Field Studies ◽  
Integrated System ◽  
Management Support ◽  
Individual System ◽  
Management Support Systems ◽  
Independent Effects ◽  
Decision Making Support

Contemporary decision-making support systems (DMSSs) are large systems that vary in nature, combining functionality from two or more classically defined support systems, often blurring the lines of their definitions. For example, in practical implementations, it is rare to find a decision support system (DSS) without executive information system (EIS) capabilities or an expert system (ES) without a recommender system capability. Decision-making support system has become an umbrella term spanning a broad range of systems and functional support capabilities (Alter, 2004). Various information systems have been proposed to support the decision-making process. Among others, there are DSSs, ESs, and management support systems (MSSs). Studies have been conducted to evaluate the decision effectiveness of each proposed system (Brown, 2005; Jean-Charles & Frédéric, 2003; Kanungo, Sharma, & Jain, 2001; Rajiv & Sarv, 2004). Case studies, field studies, and laboratory experiments have been the evaluation vehicles of choice (Fjermestad & Hiltz, 2001; James, Ramakrishnan, & Kustim, 2002; Kaplan, 2000). While for the most part each study has examined the decision effectiveness of an individual system, it has done so by examining the system as a whole using outcome- or user-related measures to quantify success and effectiveness (Etezadi-Amoli & Farhoomand, 1996; Holsapple & Sena, 2005; Jain, Ramamurthy, & Sundaram, 2006). When a study has included two or more systems, individual system effects typically have not been isolated. For example, Nemati, Steiger, Lyer, and Herschel (2002) presented an integrated system with both DSS and AI (artificial intelligence) functionality, but they did not explicitly test for the independent effects of the DSS and AI capabilities on the decision-making outcome and process. This article extends the previous work by examining the separate impacts of different DMSSs on decision effectiveness.

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