Means of achieving Business Process Management success factors

Business Process Management (BPM) in recent years has become a highest priority area for most organizations. Since this concept is multidisciplinary, success in this endeavour requires considering different factors. A number of studies have been conducted to identify these factors; however, most are limited to the introduction of high-level factors or to the identification of the means of success within only a specific context. This paper presents a holistic framework of success factors as well as the associated means for achieving success. This framework introduces nine factors, namely culture, leadership, communication, Information Technology, strategic alignment, people, project management, performance measurement and methodology. Each of these factors are characterized further by defining some sub-constructs and under each sub construct the means for achieving success are also introduced. This framework including means for achieving success can be useful for BPM project stakeholders in adequately planning the initiative and checking the progress during the implementation.

A proposed role for models and simulations in management research

Overall, computer models and simulations have a rather disappointing record within the management sciences as a tool for predicting the future. Social and market environments can be influenced by an overwhelming number of variables, and it is therefore difficult to use computer models to make forecasts or to test hypotheses concerning the relationship between individual behaviours and macroscopic outcomes. At the same time, however, advocates of computer models argue that they can be used to overcome the human mind's inability to cope with several complex variables simultaneously or to understand concepts that are highly counterintuitive. This paper seeks to bridge the gap between these two perspectives by suggesting that management research can indeed benefit from computer models by using them to formulate fruitful hypotheses.

Exposure risk assessment and evaluation of the best management practice for controlling pesticide runoff from paddy fields. Part 2: Model simulation for the herbicide pretilachlor

BACKGROUND: Monitoring studies revealed high concentrations of pesticides in the drainage canal of paddy fields. It is important to have a way to predict these concentrations in different management scenarios as an assessment tool. A simulation model for predicting the pesticide concentration in a paddy block (PCPF-B) was evaluated and then used to assess the effect of water management practices for controlling pesticide runoff from paddy fields. RESULTS: The PCPF-B model achieved an acceptable performance. The model was applied to a constrained probabilistic approach using the Monte Carlo technique to evaluate the best management practices for reducing runoff of pretilachlor into the canal. The probabilistic model predictions using actual data of pesticide use and hydrological data in the canal showed that the water holding period (WHP) and the excess water storage depth (EWSD) effectively reduced the loss and concentration of pretilachlor from paddy fields to the drainage canal. The WHP also reduced the timespan of pesticide exposure in the drainage canal. CONCLUSIONS: It is recommended that: (1) the WHP be applied for as long as possible, but for at least 7 days, depending on the pesticide and field conditions; (2) an EWSD greater than 2 cm be maintained to store substantial rainfall in order to prevent paddy runoff, especially during the WHP.

Recommendations from analyzing the state-of-the-art of business process management research

Business Process Management (BPM) as a research field integrates different perspectives from the disciplines computer science, management science and information systems research. Its evolution has by been shaped by the corresponding conferences series, the International Conference on Business Process Management (BPM conference). As much as in other academic discipline, there is an ongoing debate that discusses the identity, the quality and maturity of the BPM field. In this paper, we review and summarize the major findings a larger study that will be published in the Business & Information Systems Engineering journal in 2016. In the study, we investigate the identity and progress of the BPM conference research community through an analysis of the BPM conference proceedings. Based on our findings from this analysis, we formulate recommendations to further develop the conference community in terms of methodological advance, quality, impact and progression.

The distribution of the sample minimum-variance frontier

In this paper, we present a finite sample analysis of the sample minimum-variance frontier under the assumption that the returns are independent and multivariate normally distributed. We show that the sample minimum-variance frontier is a highly biased estimator of the population frontier, and we propose an improved estimator of the population frontier. In addition, we provide the exact distribution of the out-of-sample mean and variance of sample minimum-variance portfolios. This allows us to understand the impact of estimation error on the performance of in-sample optimal portfolios. Key Words: minimum-variance frontier; efficiency set constants; finite sample distribution

Improving detection probabilities for pests in stored grains

BACKGROUND: The presence of insects in stored grains is a significant problem for grain farmers, bulk grain handlers and distributors worldwide. Inspections of bulk grain commodities is essential to detect pests and therefore to reduce the risk of their presence in exported goods. It has been well documented that insect pests cluster in response to factors such as microclimatic conditions within bulk grain. Statistical sampling methodologies for grains, however, have typically considered pests and pathogens to be homogeneously distributed throughout grain commodities. In this paper we demonstrate a sampling methodology that accounts for the heterogeneous distribution of insects in bulk grains. RESULTS: We show that failure to account for the heterogeneous distribution of pests may lead to overestimates of the capacity for a sampling program to detect insects in bulk grains. Our results indicate the importance of the proportion of grain that is infested in addition to the density of pests within the infested grain. We also demonstrate that the probability of detecting pests in bulk grains increases as the number of sub-samples increases, even when the total volume or mass of grain sampled remains constant. CONCLUSION: This study demonstrates the importance of considering an appropriate biological model when developing sampling methodologies for insect pests. Accounting for a heterogeneous distribution of pests leads to a considerable improvement in the detection of pests over traditional sampling models.

Communications and learning structures that facilitate transfer of knowledge at innovation transition points

Innovation processes are rarely smooth and disruptions often occur at transition points were one knowledge domain passes the technology on to another domain. At these transition points communication is a key component in assisting the smooth hand over of technologies. However for smooth transitions to occur we argue that appropriate structures have to be in place and boundary spanning activities need to be facilitated. This paper presents three case studies of innovation processes and the findings support the view that structures and boundary spanning are essential for smooth transitions. We have explained the need to pass primary responsibility between agents to successfully bring an innovation to market. We have also shown the need to combine knowledge through effective communication so that absorptive capacity is built in process throughout the organisation rather than in one or two key individuals.

Modeling train delays in urban networks

The reliability of urban passenger trains is a critical performance measure for passenger satisfaction and ultimately market share. A delay to one train in a peak period can have a severe effect on the schedule adherence of other trains. This paper presents an analytically based model to quantify the expected positive delay for individual passenger trains and track links in an urban rail network. The model specifically addresses direct delay to trains, knock-on delays to other trains, and delays at scheduled connections. A solution to the resultant system of equations is found using an iterative refinement algorithm. Model validation, which is carried out using a real-life suburban train network consisting of 157 trains, shows the model estimates to be on average within 8% of those obtained from a large scale simulation. Also discussed, is the application of the model to assess the consequences of increased scheduled slack time as well as investment strategies designed to reduce delay.

What is a good project manager? Reconceptualizing the “do” : an Aristotelian perspective

In Social Science (Organization Studies, Economics, Management Science, Strategy, International Relations, Political Science…) the quest for addressing the question “what is a good practitioner?” has been around for centuries, with the underlying assumptions that good practitioners should lead organizations to higher levels of performance. Hence to ask “what is a good “captain”?” is not a new question, we should add! (e.g. Tsoukas & Cummings, 1997, p. 670; Söderlund, 2004, p. 190). This interrogation leads to consider problems such as the relations between dichotomies Theory and Practice, rigor and relevance of research, ways of knowing and knowledge forms. On the one hand we face the “Enlightenment” assumptions underlying modern positivist Social science, grounded in “unity-of-science dream of transforming and reducing all kinds of knowledge to one basic form and level” and cause-effects relationships (Eikeland, 2012, p. 20), and on the other, the postmodern interpretivist proposal, and its “tendency to make all kinds of knowing equivalent” (Eikeland, 2012, p. 20). In the project management space, this aims at addressing one of the fundamental problems in the field: projects still do not deliver their expected benefits and promises and therefore the socio-economical good (Hodgson & Cicmil, 2007; Bredillet, 2010, Lalonde et al., 2012). The Cartesian tradition supporting projects research and practice for the last 60 years (Bredillet, 2010, p. 4) has led to the lack of relevance to practice of the current conceptual base of project management, despite the sum of research, development of standards, best & good practices and the related development of project management bodies of knowledge (Packendorff, 1995, p. 319-323; Cicmil & Hodgson, 2006, p. 2–6, Hodgson & Cicmil, 2007, p. 436–7; Winter et al., 2006, p. 638). Referring to both Hodgson (2002) and Giddens (1993), we could say that “those who expect a “social-scientific Newton” to revolutionize this young field “are not only waiting for a train that will not arrive, but are in the wrong station altogether” (Hodgson, 2002, p. 809; Giddens, 1993, p. 18). While, in the postmodern stream mainly rooted in the “practice turn” (e.g. Hällgren & Lindahl, 2012), the shift from methodological individualism to social viscosity and the advocated pluralism lead to reinforce the “functional stupidity” (Alvesson & Spicer, 2012, p. 1194) this postmodern stream aims at overcoming. We suggest here that addressing the question “what is a good PM?” requires a philosophy of practice perspective to complement the “usual” philosophy of science perspective. The questioning of the modern Cartesian tradition mirrors a similar one made within Social science (Say, 1964; Koontz, 1961, 1980; Menger, 1985; Warry, 1992; Rothbard, 1997a; Tsoukas & Cummings, 1997; Flyvbjerg, 2001; Boisot & McKelvey, 2010), calling for new thinking. In order to get outside the rationalist ‘box’, Toulmin (1990, p. 11), along with Tsoukas & Cummings (1997, p. 655), suggests a possible path, summarizing the thoughts of many authors: “It can cling to the discredited research program of the purely theoretical (i.e. “modern”) philosophy, which will end up by driving it out of business: it can look for new and less exclusively theoretical ways of working, and develop the methods needed for a more practical (“post-modern”) agenda; or it can return to its pre-17th century traditions, and try to recover the lost (“pre-modern”) topics that were side-tracked by Descartes, but can be usefully taken up for the future” (Toulmin, 1990, p. 11). Thus, paradoxically and interestingly, in their quest for the so-called post-modernism, many authors build on “pre-modern” philosophies such as the Aristotelian one (e.g. MacIntyre, 1985, 2007; Tsoukas & Cummings, 1997; Flyvbjerg, 2001; Blomquist et al., 2010; Lalonde et al., 2012). It is perhaps because the post-modern stream emphasizes a dialogic process restricted to reliance on voice and textual representation, it limits the meaning of communicative praxis, and weaking the practice because it turns away attention from more fundamental issues associated with problem-definition and knowledge-for-use in action (Tedlock, 1983, p. 332–4; Schrag, 1986, p. 30, 46–7; Warry, 1992, p. 157). Eikeland suggests that the Aristotelian “gnoseology allows for reconsidering and reintegrating ways of knowing: traditional, practical, tacit, emotional, experiential, intuitive, etc., marginalised and considered insufficient by modernist [and post-modernist] thinking” (Eikeland, 2012, p. 20—21). By contrast with the modernist one-dimensional thinking and relativist and pluralistic post-modernism, we suggest, in a turn to an Aristotelian pre-modern lens, to re-conceptualise (“re” involving here a “re”-turn to pre-modern thinking) the “do” and to shift the perspective from what a good PM is (philosophy of science lens) to what a good PM does (philosophy of practice lens) (Aristotle, 1926a). As Tsoukas & Cummings put it: “In the Aristotelian tradition to call something good is to make a factual statement. To ask, for example, ’what is a good captain’?’ is not to come up with a list of attributes that good captains share (as modem contingency theorists would have it), but to point out the things that those who are recognized as good captains do.” (Tsoukas & Cummings, 1997, p. 670) Thus, this conversation offers a dialogue and deliberation about a central question: What does a good project manager do? The conversation is organized around a critic of the underlying assumptions supporting the modern, post-modern and pre-modern relations to ways of knowing, forms of knowledge and “practice”.

Sampling stored-product insect pests : a comparison of four statistical sampling models for probability of pest detection

Background: Developing sampling strategies to target biological pests such as insects in stored grain is inherently difficult owing to species biology and behavioural characteristics. The design of robust sampling programmes should be based on an underlying statistical distribution that is sufficiently flexible to capture variations in the spatial distribution of the target species. Results: Comparisons are made of the accuracy of four probability-of-detection sampling models - the negative binomial model,1 the Poisson model,1 the double logarithmic model2 and the compound model3 - for detection of insects over a broad range of insect densities. Although the double log and negative binomial models performed well under specific conditions, it is shown that, of the four models examined, the compound model performed the best over a broad range of insect spatial distributions and densities. In particular, this model predicted well the number of samples required when insect density was high and clumped within experimental storages. Conclusions: This paper reinforces the need for effective sampling programs designed to detect insects over a broad range of spatial distributions. The compound model is robust over a broad range of insect densities and leads to substantial improvement in detection probabilities within highly variable systems such as grain storage.

Application of lean production to reducing operational waste in a tile manufacturing process

Roofing tile manufacturing is a mass production process with high operational and inventory wastes and costs. Due to huge operational costs, excessive inventory and wastes, and quality problems, roofing tile manufacturers are trying to implement lean manufacturing practice in their operations in order to remain competitive in an ncreasingly competitive global market. The aim of this research is to evaluate the possibility of reducing the operational and inventory costs of the tile manufacturing process through waste minimization. This paper analyses the current waste situation in a tile manufacturing process and develops current and future value stream mapping for such a process with a view to implementing lean principles in manufacturing. The focus of the approach is on cost reduction by eliminating non-value-added activities.

A multidimensional model of client success when engaging external consultants

Too often the relationship between client and external consultants is perceived as one of protagonist versus antogonist. Stories on dramatic, failed consultancies abound, as do related anecdotal quips. A contributing factor to many "apparently" failed consultancies is a poor appreciation by both the client and consultant of the client's true goals for the project and how to assess progress toward these goals. This paper presents and analyses a measurement model for assessing client success when engaging an external consultant. Three main areas of assessment are identified: (1) the consultant;s recommendations, (2) client learning, and (3) consultant performance. Engagement success is emperically measured along these dimensions through a series of case studies and a subsequent survey of clients and consultants involved in 85 computer-based information system selection projects. Validation fo the model constructs suggests the existence of six distinct and individually important dimensions of engagement success. both clients and consultants are encouraged to attend to these dimensions in pre-engagement proposal and selection processes, and post-engagement evaluation of outcomes.

Hydrolysis of triasulfuron, metsulfuron-methyl and chlorsulfuron in alkaline soil and aqueous solutions

The hydrolysis of triasulfuron, metsulfuron-methyl and chlorsulfuron in aqueous buffer solutions and in soil suspensions at pH values ranging from 5.2 to 11.2 was investigated. Hydrolysis of all three compounds in both aqueous buffer and soil suspensions was highly pH-sensitive. The rate of hydrolysis was much faster in the acidic pH range (5.2-6.2) than under neutral and moderately alkaline conditions (8.2-9.4), but it increased rapidly as the pH exceeded 10.2. All three compounds degraded faster at pH 5.2 than at pH 11.2. Hydrolysis rates of all three compounds could be described well with pseudo-first-order kinetics. There were no significant differences (P =0.05) in the rate constants (k, day-1) of the three compounds in soil suspensions from those in buffer solutions within the pH ranges studied. A functional relationship based on the propensity of nonionic and anionic species of the herbicides to hydrolyse was used to describe the dependence of the 'rate constant' on pH. The hydrolysis involving attack by neutral water was at least 100-fold faster when the sulfonylurea herbicides were undissociated (acidic conditions) than when they were present as the anion at near neutral pH. In aqueous buffer solution at pH > 11, a prominent degradation pathway involved O-demethylation of metsulfuron-methyl to yield a highly polar degradate, and hydrolytic opening of the triazine ring. It is concluded that these herbicides are not likely to degrade substantially through hydrolysis in most agricultural (C) 2000 Society of Chemical Industry.