MIS, technology adoption, managerial decisionmaking
Management Information Systems is a system that converts data into information, communicated in an appropriate form to managers at levels of an organization. The information can contribute to effective decisionmaking or planning to be carried out (Patterson, 2005). MIS basically involves the process of collecting, processing, storing, retrieving and communicating the relevant information for the purpose of efficient management operations and for business planning in any organizations.
MIS, technology adoption, managerial decisionmaking
Management Information Systems is a system that converts data into information, communicated in an appropriate form to managers at levels of an organization. The information can contribute to effective decisionmaking or planning to be carried out (Patterson, 2005). MIS basically involves the process of collecting, processing, storing, retrieving and communicating the relevant information for the purpose of efficient management operations and for business planning in any organizations. Thus, the success of effective decision-making, is consider as the heart of administrative process, is highly dependent partly on available information, and partly on the functions that are the components of the process (Nath & Badgujar, 2013). MIS Provide information in the form of pre specified reports and displays to support business decisionmaking (O’Brien & George, 2007).MIS is define as type of information systems that transform data to information and summarized the information to Meaningful and useful forms as management reports to use it in managerial decisionmaking. Figure 1 show the relationship between management information systems and decision-making. The problem is that no documented evaluation model to evaluate the success of MIS. In addition the existing IS success model only focus on technology. Therefore, there
1 Mechanical Engineering Department, Petra Christian University Jalan Siwalankerto 121-131 Surabaya, Indonesia
Abstract— Closed-loop supply chain has gained a significant attention during the recent decades since there is an increased awareness toward sustainable development. However, the implementation of closed-loop supply chain is confronted with numerous barriers and challenges due to uncertainties in input as well as in process. In contrast to manufacturing process where the input is mostly homogeneous raw material, the reverse chain’s input comes from product’s end-of-use or end-of-life; therefore the timing, quality and quantity are uncertain. The recovery process also brings other challenges due to various quality grades of the product returns and various recovery options. On the other hand, information technology has been studied extensively in relation to supply chain management. Most of the works show that the use of information technology could enhance supply chain performance. However, the study on the importance of information technology in closed-loop supply chain is still limited. In this paper, we discuss the role of information technology and then propose a conceptual framework of decisionmaking in adopting IT in closed-loop supply chain management. We propose a conceptual framework for IT adoptiondecisionmaking with four essential key attributes that are evaluated for each of the closed-loop supply chain activities
the provisioning IT services (Kauffman et al., 2014). Today, there are three main classes of model for the delivery of IT services; in-house provision, traditional outsourcing and cloud computing, which is sometimes also seen as a form of outsourcing. The literature shows that there is little research that focuses on supporting decisionmaking during the cloud computing adoption process (Alshamaila et al., 2013; Azeemi et al., 2013; Gonzenbach et al., 2014). The primary research identified that a lack of understanding of the issues affecting cloud computing was one of the factors which inhibited cloud adoption. Chang et al. (2013) argued that a structured approach is necessary to manage the challenge of adopting new technology. As discussed in chapter three, we propose in this thesis that cloud computing adoption should be supported by a structured approach based on KM and OL. The process of cloud adoptiondecisionmaking tends to be ad hoc in enterprises. The existing models and frameworks discussed as part of the literature review do not cover all aspects of cloud adoption and do not guide decision makers on deciding between the different factors. This chapter presents a Knowledge Management Based framework to support decisionmaking for Cloud Computing adoption. The framework takes account of the range of factors that influence decisionmaking for cloud adoption and can be customised to meet the needs of organisations and decision makers, meaning that the Framework is generalisable to different contexts and different technical and organisational environments.
cloud computing. This is the major driver for research towards developing a decision model for cloud adoption.
Kundra (2012) designed a decision framework for U.S federal agencies planning to adopt cloud environment. The Federal cloud computing framework according to Kundra (2012) involves three stages: Select Provision and Manage. Kundra (2012) has designed this framework from a federal agencies point of view on how to plan a successful migration. The essential factors that are needed to be addressed are listed as guidelines and these can be used by any organisation to evaluate if their existing IT system is ready for cloud deployment. It is clear that in this model it is assumed that adapting to a cloud infrastructure is cost effective and the IT infrastructure in U.S can support the technology. The major drawback of this framework is that it cannot be applied to SMEs regardless of the geographical location as cost benefits are very important for SMEs. The infrastructure in place in Tamil Nadu may not support cloud services as penetration of broadband services in rural areas are very less and internet access are available only through 3G and 4G services. The cost of high bandwidth will be an important factor in such circumstances.
Among the social variables, education, experience, production knowledge and awareness significantly influence adoption of cross-bred cows. Family size and number of relatives are negatively correlated with adoption. Several studies have documented that households who are actively involved in social networks are better insured against unforseen risks of failures or financial losses than households who are less involved in social networks and have few relatives (Barlett, 1980). Nevertheless, there is a limit to the insurance that relatives or networks can provide against risks of crop or livestock losses. Cross-bred cows or purchases of livestock, in general, are risky investments. Households may not be completely buffered from financial risk associated with adoption of cross-bred cows. Thus, they may decide to take responsibility for the consequences of their investment decision. Another interpretation for the negative effect of family size and relatives on the adoption of cross-bred cows is that if households invest in expensive innovations, they may not have sufficient financial or physical resources to participate in social-networks. They may not help relatives and provide subsistence requirements for their families. Therefore, increases in family size and relatives may negatively influence decisions regarding adoption of cross-bred cows.
According to controller and top manager opinions, it is very important to emphasize that economical and organizational management has to be part of the managerial appointment; consequently the economical expectations of lead physicians are clearly rising. In many institutions the physicians still do not understand the role and content of controlling reports, for which the only solution is the joint work of economic and medical units. Several top and middle managers question the validity of data, typically costs but the answer is, again, the development of controlling systems. There is more opportunity in controlling but to explore them, widening and sharing knowledge and the adoption of the systems are all essential.
2.1.1 Research philosophy and approach
Research philosophy forms the outermost layer of the research onion. In general, phi- losophy can be defined, as the questioning of the basic fundamental concepts and the need to embrace a meaningful understanding of a particular field. (Burke, 2007) The research philosophy comprises important assumptions about the way people view the world and the relation to the development and nature of knowledge. Generally, there are three main ways of thinking about research philosophy: epistemology, ontology and ax- iology. Epistemology relates to what constitutes acceptable knowledge in the field of study. Ontology studies the questions of the assumptions researchers have about the way the world operates and the commitment held to particular views – the nature of reality. Axiology is concerned with judgements about values. It would be misleading to assume one research philosophy is better than the other, they are better at doing differ- ent things. Hence, the adoption of the right research philosophy depends on the research question that a researcher is seeking to answer. However, the practical reality is that a particular research question rarely falls neatly into only one philosophical domain.
etc. and successful ones. In all cases, the accountants have collected, analyzed interpreted, presented and communicated the information for the use of interested parties. It remains the adoption, application and implementation of that information for the benefit of the organization. If these were being done as and when due, then the failures in the business sector and even domestic government would not have been. So the problem is, if interested users are actually aware of this various accounting information and if they apply it in their production or investment decisionmaking process; can decision based on accounting information actually raise efficiency level via cost minimization and wealth maximization?
with a sustained growth. Sometimes, avoiding decisionmaking seems easier, especially, when you get into a lot of confrontation after making the tough decision. But, making the decisions and accepting its consequences is the only way to stay in control of your corporate life and time.
Resources are key force multipliers of postindustrial information society and therefore the creation of a knowledge management information system will create good advantage in increasing the efficiency and competitiveness in comparison with the previous centralized systems where communication between subsystems has been more difficult i.e.
Our approach allows a certain flexibility as to which revealed priors are compatible with the information: this is important as it leaves room to model different attitudes towards imprecision, and allows for decisions that are not necessarily biased towards extreme conservatism. Take for instance the global warming problem. Scientific evidence has somewhat restricted the set of possible values for important parameters, without being able, at this stage, to actually assess what are the exact effects of emission of various gas on the average temperature. Taking this ev- idence into account and applying the maxmin expected utility approach would then “uniquely”
The article draws out a number of observations. The simple presumption that individuals wish to have or need information to assist them in their decisionmaking is misplaced. Psychological factors such as habit and satisficing behaviour can obviate the need for information. Inertia and mental effort can inhibit actions to review the relative merits of alternative travel choices. The need and hence demand for information is much more limited. In addition, even when information is sought, it may be for confirmatory reasons rather than for reasons of comparison – in other words it can provide assistance to the individual in planning the detail of and executing their journey whilst not bringing about any change in behaviour as such. The offering of information services itself has advanced substantially in the last 10 years, boosted notably by advances in ICT and specifically the mainstreaming of Internet and mobile telephony. Indications of high usage levels of some services would suggest that while information services are not in high demand for a large proportion of journeys, this should not be misconstrued as an absolute indication of low demand. There is a significant minority of journeys for which information can prove highly useful to the individual. The extent to which, however, usefulness to the individual equates to behaviour change by the individual is not clear though it seems that substantial behaviour change (certainly in terms of mode choice) is unlikely. Insights from this article it is hoped will serve as a safeguard against technologically deterministic and thus utopian outlooks for the future of travel information provision. There are still strong temptations evident in the literature to sweep aside the barriers with a speculative view that everything can be solved by ‘clever’, personalised information services, made possible through technological advance and ingenuity. Some of the barriers, it is true, are technological in nature, but other more challenging ones concern human nature and indeed the availability of and relative merits of actual travel options. As we move into the future, technological advance will doubtless occur, but fundamental traits of human behaviour and information seeking are likely to remain much more fixed.
organized to house and foster specialized expertise. The very term itself “expert group”, should indicate that these are groups composed by technocratic and scientific experts.
The claim to autonomy and influence in a political system is intricately linked to its ability to present itself as neutral, grounding its acts and actions on updated and specialized information. The administration is seen as deriving its legitimacy from principles of enlightened, knowledge-based government (Olsen, 2008b: 17). Being seen by other actors as incompetent, unprofessional and uninformed is then anathema. Yet, bureaucratic organisations have limited resources as repositories of knowledge and for gathering and processing new specialised information by themselves. Hence we would expect them to seek their informational partners in the institutions that embody the neutral professional-technical expertise more than any other, i.e. the scientific-academic community that represent the ultimate long-term specialization of knowledge. Expertise is then understood as scientific information produced and validated through the scientific method that ensures impartial information into the policy making process.
Furthermore, Sargent classifies a framework for taking and implementing decision into five steps:
considering, consulting, deciding, communicating, and checking (Sargent, 1976: 8-9). The first step is the preparation step at which managers consider as the problem. In this case, the problem should be clarified by checking for the cause or effect and be sure it is their own decision to take. Ultimate objective, time, and other constraints should be clarified as well. Thus, managers have to decide what information is really needed. The second step is to consult the other people. In this step, managers should make maximum amount of information available. In other words, they have to collect the facts relating to the problems. In this stage, it is necessary to take the initiative to involve those affected. The third step is consultation in order to get some options. Based on the real problem and think whether or not the decision can be implemented. If it can be implemented, the implemented plan should be written down. The fourth step, managers has to explain what decision has been decided, what will happen, why, and to whom it will affect. The decision must be informed to the subordinates. To be remembered, a briefing in group should be given. It is not effective to give briefing individually, but in group. Managers should ensure that everyone understands when the decision will be implemented. The final step, managers should check what happens after putting the decision into effect, whether or not it will positively affect everyone and everything in the organization. Thus, the decision needs to be reviewed and corrected if necessary. If something wrong happens, a correction should be made.
As public organizations, Departments of Transportation (DOTs) are information- intensive environments. DOTs are the places where thousands of transportation professionals need resources, capabilities, coordination, and knowledge to forge together large volumes of data from disparate sources with human insight and expertise to solve critical problems necessary to serve the public’s transportation needs. The public is demanding greater safety while traveling, requiring more research and development into safe driving, accident prevention measures, and homeland security protection. DOTs are delivering more services through open government initiatives on-line using Internet and mobile services to fulfill emerging strategies at the federal, state, and local levels increasing transparency, participation, collaboration, and innovation. Rapid changes in the Internet and computer technologies are enabling the delivery of government services.
Ratios of financial statement analysis and the business decision
Ratio is rational or relative number which means that one economic value is put into relation (it is being divided) with other economic value. Since there is no sense in connecting any two economi- cal values, we can speak about prerequisites of ratio’s accuracy. Considering the time dimension, financial ratios can be basically divided into two groups. One group of financial ratios includes company’s business within the particular time period (usually a year). This group is based on the data from profit and loss account and cash flow statement. The other group of financial ratios re- fers to the exactly defined moment which corresponds with the balance sheet date and talks about company’s financial position in that moment. Ratios contain concentrated information that is needed for business quality measurement and decisionmaking process as well.
There are a number of decision support systems. These can be categorized into five types: communications driven DSS, data driven DSS, document driven DSS, knowledge driven DSS and model driven DSS. A communication driven DSS supports more than one person working on a shared task. Many collaborators work together to come up with a series of decision to set in motion a solution or strategy. Most communications driven DSSs are targeted at internal teams, including partners. The most commons technology used to deploy the DSS is a web or a client server. In general, groupware, bulletin boards, audio and video conferencing are the primary technologies for communication driven decision support. Data driven DSS model puts its emphasis on collected data that is then manipulated to fit the decision maker’s needs. This data can be internal, external and in a variety of formats. This model emphasizes access to and manipulation of a time series of internal company data and sometimes external and real time data. Simple file systems accessed by query and retrieval tools provide the most elementary level of functionality. Most data driven DSSs are targeted at managers, staff and also product / service suppliers. It is used to query a database or data warehouse to seek specific answers for specific purposes. It is deployed via a main frame system, client server link or via web. Document driven DSSs are more common, targeted at a broad base of user groups. The purpose of such a decision support system is to search web pages and find documents on a specific set of keywords or search terms. This model uses computer storage and
In the present article the authors discuss two kinds of information systems, namely, MIS, and DSS, and then their characteristics, interrelationship and their relations with decision-making process in an organization.
In the 1950s, Herbert Simon and James March for the first time introduced a different decisionmaking framework for understanding organizational behavior. Although they labored on the bureaucratic model by emphasizing on individual work in rational organizations and thus behaving rationally, their model added a new dimension: The idea that a human being’s rationality is limited. By offering a more realistic alternative to classical assumption of rational in decision-making, this model supported the behavioral view of individual and organizational functioning. The model suggested that when an individual makes decision, he examines a limited set of possible alternatives rather than all available options. “He accepts satisfactory or good enough” choices, rather than insist on optimal choices. He makes choices that are good enough because he does not search until he finds perfect solution to a problem (Gordon, 1993). Simon divided kinds of decisions into two basic types: programmed and non programmed decisions.
A career in private accounting means providing accounting services to the com- pany that employs you. Every major company in the world hires accountants. Just think of all the accounting issues at Dell , for example. Dell, and all other large companies, need accountants with training and experience in financial accounting, management accounting, taxation, internal auditing, and accounting information systems. Whereas working as a public accountant provides the advantage of expe- rience working with a number of different clients, private accountants sometimes earn higher starting salaries. In fact, many accounting students begin their careers in public accounting, gaining experience across a wide array of companies and industries, and then eventually switch over to one of their favorite clients as private accountants. Other students take positions directly in private accounting right out of college.