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Hi there,
through my research, I am more and more coming to the conclusion that the contexts of corporate change turn out to be essential. For example, a transformation in agriculture is regulated quite differently than in the aerospace industry. In a recent presentation by Daimler's CEO, this aspect was emphasized in particular (ecosystems, increasing networking, etc.).
Beyond the ambiguous definitions of change, there are, as you surely know, various approaches to characterizing corporate change. One comprehensive approach is presented by Albach et al. 2014 (https://t1p.de/rk70), see appendix.
There are also characterizations for economic activities, the International Standard Industrial Classification of All Economic Activities, both as a broad and very detailed industry specification: https://t1p.de/7cth
Do you know if there is already research in this area? Which disciplines are addressing the question of how industry contexts (macro) influence corporate change (micro)?
Certainly, it is not possible to cover all industries, but is there, for example, research in the context of C - Manufacturing? How do the industry-specific characteristics of the manufacturing industry affect corporate change projects? Are there certain change characteristics (features, certain dynamics, etc.) that are always expressed in the same way on a broad or detailed industry classification?
How would you proceed methodically with the investigation? I thought first of all of an investigation of the rough structure, e.g. expert interviews and a subsequent survey? Feel free to "brainstorm" as an answer as well.
Thank you and best Greetings from Aachen, Germany
Alexander Kwiatkowski
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In addition to Weill and Ross in “IT Savvy," see their "Enterprise Architecture As Strategy: Creating a Foundation for Business Execution" as well as Ross et al's more recent "Designed for Digital: How to Architect Your Business for Sustained Success" (see my review) https://www.amazon.com/gp/customer-reviews/R33HX594W0I7TL?ref=pf_ov_at_pdctrvw_srp
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I have sales data set of 120 months and it is associated with ARCH effect. Is there any procedure to predict the future sales (for next 12 months) using this data set by incorporating ARCH effect? The identified model is GARCH(2,1).
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The hybrid model ARIMA-GARCH or ARMA-GARCH is used to predict the future behavior. It is simple that you can add the volatility to the predicted future values with the ARIMA or ARMA processes.
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Types like; Job Shop, Batch Production, Mass Production, Manual Line Production. and why?
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mass production, manual assembly line.
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In design and construction, there are many factors that can influence the occurrence of technical risk, which, as a consequence, affects the duration, quality and cost.
Technical risk is risk due to technical factors.
Example:
1. Low qualification of a specialist leads to low quality of project documentation.
2. Lack of BIM department.
3. Location of the facility (remoteness from the main manufacturing plants, difficulty in transporting equipment, etc.)
4.Use of new technologies, etc.
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For design and construction of a building. I recommend you the work on the risks existing in the interactions Human - Means, Human - Methods and Human - Work Environment. These are the risks due to ergonomic hazards (Ergonomic Factors). Good luck.
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Is Research in Industrial Management or Agricultural Management:
(Sustainable Supply Chain Network model of perishable agricultural products)
Research done?
Can you guide?
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با سلام به فصلنامه مدیریت صنعتی دانشگاه تهران رجوع کنید بیشترین مقالات فارسی داخل کشوری در زمینه مدیریت زنجیره تامین اونجا بچاپ رسیدن و در زمینه راهنمایی بهتر دکتر یزدی دانشگاه شریف بهترین گزینه هستند
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Aggflow & Metsim Softwares, using fields and benefits of these softwares.
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Aggflow is good for the simulation of aggregates or solids material flow for processes such as material handling, screening, crushing, etc. It is not recommended for complex processes containing slurries and thermodynamics. METSIM is good for both material handling and process plant (mill, flotation, hydromet, pyromet). It does good heat and mass balance. But METSIM is not used in coal processing. LIMN is popular in coal processing and is now getting popularity in milling, hydromet, and pyromet.
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The connectivity of flows can it be always related to the  NTIC or it can exceed it ? How can we see it in the automotive industry? what are the major problems of this particular domaine that needs to be devolopped to have an efficient and a performent SC
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A very interesting topic of research .
Logistics flow in Supply chain can be studied using advanced analytics, simulation and modeling tools. for instance Arena Supply Chain Simulation Software.
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That case occurs in different European countries but not in Germany? What are the main reasons?
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Low cost of production (e.g., cheap labour, low tax, etc.) is part of the reasons.
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I'm doing a research within a MTO environment. The capacity levels within this company are based on historical data. The order realization of past year is used as input for the "product mix (named by the company)" to measure capacity and set capacity levels for the next year, on product family level (in volume).
When the product mix change time over time, due to the MTO environment, the historical data (the product mix) is not representative for future demand. So, the capacity levels are not reliable what results in lower operations performance and accepting too much or too less orders.
Do any of you know a approach of method to determine these capacity levels in a MTO environment or how to calculate this product mix in MTO. Could this by using e.g. forecast techniques? Sources that wrote about this topic are scarce.
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Dear Michiel
it is complex to model and measure production capacity in MTO environments.
First of all let's talk about the model. I invite you to refer to the model of Grando & Turco, that you can find here:
Grando*, A., and F. Turco. "Modelling plant capacity and productivity: conceptual framework in a single-machine case." Production Planning & Control 16.3 (2005): 309-322.
This model defines the production capacity of a plant in a period of time (quantity / period) as the multiplication of the following 3 effects:
- the velocity, or rate (pieces / hour)
- the time used to produce (hours / period)
- the yield of the process (%)
Given that you can manufacture so differtiated products, in a MTO context it is better to define and measure the production capacity as hours / period => you don't need the first term, but just the other two.
So, in practice in order to correctly measure the available production capacity it is important to:
a). identify the bottleneck resource within the system - be careful because it can be either a specific machine or a type of resource (often labor)
b). evaluate the limitations existing on this resource's availability, and any potential elasticity in them. For instance, about labor you can have a limited amount of people, maybe with fixed competences and worktime, but you typically always have somebody that shares more than one competence (and so can perform several different jobs) and somebody that is available to perform overtime shifts.
c). examine wether there are limitations to the bottleneck resource that are set by other resources. For instance, in the case of labor, when a machine breaks down, this might imply that the corresponding worker runs idle as a result. So, even if the machine availability is not a constraint in itself (since machine capacity is abundant), in that precise moment it sets a (further) limitation on the availability of labor, which in turn is the bottleneck resource.
Please, keep in mind that in TCO contexts you should typicaly plan with infinite capacity, and then adapt capacity to the time profile implied by the customers' orders portfolio. So it is of paramount mportance to keep one all the alternatives and flexibilities available, such as:
- external production as an alternative to internale
- alternative machines
- alternative bills of materials
- mutiple skills
- etc.
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Hello,
I am looking for academic resource with information about history of mass production. The time period, literature, events, etc.
Thank you all in advance
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Look at "Faster, Better, Cheaper" in the History of Manufacturing: From the Stone Age to Lean Manufacturing and Beyond (just published in August 2016)
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The location quotient is always calculated by using the number of employment. I am thinking whether it is feasible to use the number of factory establishment, instead of employment. Is there any literature I can refer to?
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I am agree with you
I suggest to you create both scenaries
1) number of employment
2)number of factory establishment
Then you can applye multi-criteria decision making methods in order to have strong evaluation on it and for it I think I can help on MCDM evalution
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The "cluster' plus a "ecosystem" become a term that could introduce a industry to a city, to link geographical concentration to a wider sense of urban environment, to connect the industrial workers to the stakeholders, to merge working with living. That is why i believe a local contexts of a place, which is accumulated by urban development trajectory, needs being taken account in most of urban studies. Particular in cultural and creative industries, because their value is generated by "people", "knowledge" and the "creativity". This also relates to how network and communities playing in a various ways to stimulate the creative economy, and to connect creative workers into potential market and client from informal network approach.
The other IP right, especially in which how IP role in the information and knowledge exchange process and how it present in the cluster ecosystem, however requires more study..  
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Hi Pei, as a starting point I would recommend reading four relevant papers about literature reviews:
Cruz and Teixeira, 2010; Martínez-Fernández, Capó-Vicedo, Vallet-Bellmunt, 2012; Lazzeretti, Sedita and Caloffi, 2014; Hervas-Oliver, Gonzalez, Caja, Sempere-Ripoll, 2015.
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If a product is launched in the market, what will be the reliability of the product? Is it 0 or 0.5 or 1 or does not exist. Please explain.
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Parag:
If you could define a reliability in terms of its constituents, such as time-span (its life time), durability, time to failures, Number of failures, functionality, predicted failure rate based on component and subsystem failure rates,  and MTBF or the mean time between failures, one could then create a normalized cumulative factor (between 0 and 1) along the lines of what is described in the following paper.
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I need general information, nothing specific..
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Thank you for the question.
Ouchi based his theory on Deming and he had based his on Maslow. So staring from the beginning the employees of the company after the basic needs have to be self confident and be able to perform their own self learning and self assessing.
According to Deming the employees have to adopt the new philosophy of a culture in which they know their responsibilities and believe in the constant improvement of their product and the quality of the product and the provided service as well as their own improvement. They have to believe in the business they will work on and look after the cost as if the business is belonging to them. They, this way, promote their loyalty to the company.
As per Z theory, they have to be provided by the company stable employment. The company has to be highly confident in the workers ability and allow them to participate in the management of the company. To be able to do this, the workers have to rotate within the company so they can have a global view of the way the business works. On their part they have to be, as they as able to self-assess, responsible for their productivity which has to be on the higher possible level and usually this is creating high satisfaction and morale.
In one phrase the employee has to feel the company as the own house and the employer to be the friend of the employee and not the boss. Workers loyal to company and company loyal to the workers.
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I dare to ask the one million dollar question (I am aware that somebody will judge me as naive). How should researchers work to strengthen the relationship between university and industry? At which level should the relationship be established? At political level between the university and the top management of the company, at several levels, at bottom level where the research and teaching projects are run? And last but not least, how important is the role of sponsorship in all this?
http://kid.item.ntnu.no/bedrifter the ICT company network at our faculty
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Letizia, that is a great question, but one with a complicated answer that depends a lot on your situation.
Some universities -- MIT in the US comes to mind -- have strong programs in place to support just that kind of industry/academic cooperation and mutual support. That's easier for a place like MIT, though, since they have a fairly huge alumni force that is in industry and can reach back into the university. So, the number of universities around the world that can do that kind of diverse top-down reach back from industry to university is fairly limited.
In the US we have a federal research funding program called STTR (Small Technology Transfer Innovation Research), which in term is part of a larger  program called SBIR/STTR, that explicitly funds small businesses that team up with a non-profit universities to do research; see https://www.sbir.gov/about/about-sttr#sttr-program for a quick overview. Every federal agency, including in particular the National Science Foundation, has their own set of initiatives and funding opportunities. While STTR does not create the partnership, it can provide a powerful incentive for small businesses to work with a university, along with some controls to make sure that the relationship doesn't turn predatory (something academics should keep in mind as a risk). In the US, small businesses often are created by the SBIR/STTR program, with academics using the funding as an opportunity to add in a business-savvy partner to help convert their work into sellable products.
I am a huge fan of SBIR/STTR, since I feel it make incredibly good use of relatively small grants of money to encourage creative folks to take their ideas to the next level of broader use, while at the same time providing the creators with an income from what they have done.
I do not know if other countries have similar programs. However, it's worth noting that at least some US SBIR/STTR work is open to universities in other countries if they are able to partner with a US firm. So, you might want to look over the web site (https://www.sbir.gov/) to see if there could be a fit for something at your university.
Finally, if you are asking as an individual researcher looking for industry cooperation and support, but do not have any specific university support for what you are doing, then bottom-up networking and finding the right connection becomes critical. To me that breaks down in most cases to two very different scenarios: Teaming with a huge corporation that needs innovative answers to hard questions, or creating your own small team of people already familiar with your work, and getting funding from either a bank or some form of venture capital.
In both cases -- teaming with a big player or forming a small company with external funding -- please be aware up front that there is a non-trivial chance that you can end up losing control of your intellectual property.
That's because both big companies and venture capitalists drive hard bargains for their support. The case of Google, in which two academics used venture funding to convert a paper on voting-by-links into an, um, rather successful commercial undertaking, was an exception. Larry and Sergey had an idea with enough value, and sufficient realistic awareness of that value, to be able to negotiate to keep control. Far more often, academics are either too optimistic about the broad commercial potential of their ideas (resulting in no deal at all) or too naive about it (resulting in losing control of the idea after it starts making money) to make good deals. There is, alas, no easy answer for that one. The ability to make good deals with industry is deeply dependent on the business skills of the academics -- which usually are not that great, since usually you don't get into research if you are more inclined to be a business person. Finding that special person whom you can both trust and who can work with the sharks can be the single most important step if you are wanting to create a small business to expand on an academic idea.
Incidentally, watching a few episodes of the American show Shark Tank is a good idea if you want to go the venture capital funding route. Those are real venture capitalists on that show, and their aggressive negotiating techniques are not just theatre -- they really do operate that way in real life.
The other side is partnering with some huge existing firm.
First, an observation: If you have the option of using government support versus big business support, e.g. for using a fabrication facility, always go with the government option. Why? Because your chances of staying in control of the destiny of your idea are almost always hugely higher with the publicly funded government option, as are your changes of keeping e.g. the right to keep publishing openly. That is one reason why I'm such a fan of SBIR/STTR, since it gives researchers a much better shot at creating fast-growing, highly competitive new companies.
The US has a law that enables the creation of Cooperative Research and Development Agreements, called CRADAs (https://en.wikipedia.org/wiki/Cooperative_Research_and_Development_Agreement), that allow research groups to partner with government labs to use their resources. When there is a government lab that has the right resources and is willing to share them via a CRADA, the academic or small business group has the advantage of largely keeping ownership (possibly with government-only sharing) of its intellectual property. A CRADA thus will in most cases make it more likely than an industry partnership that the group using it can stay in charge of its own destiny if they want to expand in the future.
Realistically, though, the number of opportunities for industrial partnering is often higher than are the federal options, and there can be some great opportunities in going that route. The main reason is that large firms often have made huge past investments in resources such as prototyping machinery and testing facilities, and may have difficulty using them to their maximum benefit. Chip fabrication, materials research, and pharmaceuticals are just a few examples of where big company may possess costly infrastructure and resources that can be of great value to academic research.
When that happens it can be an opportunity for a creative academic groups to negotiate use of that equipment, without necessarily giving away the entire farm on what they are doing. The ideal situation is one where both sides could walk away, but both would also benefit by some level of sharing -- the big company of its resources, and the academics of part (not all!) of the value of their intellectual property and any emerging patents. That's where the academics MUST go into business negotiating mode, and not just say things like "sure, you can have all the patents if we get to use your equipment."
So how does an academic go about creating a research support relationship with a huge firm? It's surprisingly simple: Call them! For a given type of research, there usually will not be that many big companies that are likely to have the resources you need, so simply making contact and explaining the kind of work you are doing is the first step. If you have choices, pick companies that have a good reputation for working openly and with researchers. Ask whether they have some of the kinds of resource you need, and after you find the right group (expect some searching around within the company by phone or email), tickle their interest with the kind of results you expect from your research. Hopefully, you can find enough mutual interest to get something going.
One warning: If your key value is some sort of singular insight, e.g. that Google idea that Larry and Sergey had about using links as votes, you may want to consider getting a patent application in before talking to a large firm, even one with a good reputation. To be blunt, I've seen more than one case where a naive researcher told some group every detail of their idea, and a couple of weeks later the group came back and said "You know it's a pretty amazing coincidence, but our research group over in Zoombali came up with _exactly_ that same idea just a couple of weeks ago, and even patented it! So sorry, we don't need you..."
I know that sounds like a joke, but except for the name of the place, it is not.
There is also a new an intriguing trend towards "innovation marketplaces" (worth Googling) in which individuals or small groups can complete to solve some kind of problem challenge. The preeminent example of that is InnoCentive (http://www.innocentive.com/), which is a collaboration of several huge firms to present challenges that individual or small teams can try to solve. It's worth a look, though my recollection is that it's an approach where you pretty much lose control of the idea after you solve the problem and get paid.
In the US there is also something called the Defense Innovation Marketplace, which I seem inadvertently to have helped create through some work I did on a similar idea many years ago, but I'm not quite sure how that one works, and it's deeply tied into US defense stuff. So, I doubt that one is an option for overseas work, but it pops up on any search about innovation marketplaces, so I should at least mention it.
Along those same lines, I like to think that someday our collective creativity will be able to expand itself in ways that enable every creative person on this planet to find and connect up with the intellectual and fiscal resources they need to solve those hard problems for which their situation and background give them special and unique expertise. We're not there, but some aspects of the web give me hope.
I hope some of the above is of some use to you. Good luck in any case, and please, keep researching and keep innovating. Universities and the many brilliant people in them are a major part of the creative heart and soul that our planet needs to navigate all of us into a safer future. The better we get at linking highly creative work so that it can make a difference, the better off we all will be.
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I was thinking about the different decision making methods under certain and uncertain conditions. My specific question is that:
As you know, we have many MCDM tools like AHP- ANP- TOPSIS- VIKOR- PROMOTHEE- MOORA- SIR and many other methods and all of them have been developed to fuzzy, type-2 fuzzy, intuitionistic fuzzy and Grey environments. Which one is really more applicable under uncertain situations? fuzzy ? type-2 fuzzy? Intuitionistic fuzzy? or Grey environment for a decision making method? I know each uncertain logic has its applications but sometimes a tiny different in collected data may causes different results by each methods.
All the ideas and comments are appreciated. Hope that all of the experts take an action to this question by following or leaving their valuable comments. 
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Dear Amin,
Its totally depend on availability of data.
you may get little help form my paper attached here.
Basically, in real world situation when DMs cannot make fuzzy membership function to represent true situation then they can go for Grey systems theory.  
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I work with sustainability impact assessment, in particular Economic and Environmental impact assessment of industrial systems' design.
Plenty of KPIs exist for such purposes, and the risk of selecting too many KPIs and/or not the right ones to properly assess/compare the cases in analysis (whichever they may be) exist in companies.
Are there any methodologies/guidelines that support stakeholders in the generation/selection of the KPIs that fit their needs best?
In addition to this, which tools beyond a measurement given by a KPI can be considered within the decision making process?
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Hello IIaria,
My research is concerned with the selection and development of KPIs for the wastewater sector.
First, I identified gaps in the existing KPI groups and developed KPIs to fill these gaps, in order to ensure that you will have all the KPIs you need.
Secondly, as you rightly say, many companies select the wrong KPIs or too many KPIs, so to counteract this I developed a short excel-based toolkit, within which, the user selects the data which they currently have available (and most importantly which is accurate) and from this the toolkit matches these data sets to the KPIs I have and presents the user with KPIs which they can actually manage and calculate over time.
It's a little removed from what you are doing but it may give you ideas. If you want you can download my publications on the topic.
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I want to develop inventory models that can handle both in-plant and purchased inventories using just-in-time concepts.
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The concept of just-in-time (JIT) delivery is generally incorporated into models by means of earliness and tardiness costs. In JIT handling of inventories you should consider penalty costs for amount of early and tardy deliveries.  See the below paper, it may help.
 An Integrated Production-Distribution Planning in Green Supply Chain: A multi-objective evolutionary approach.  
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In other words is that reasonable for industry studies to divert their focus of attention to:
1. single industry studies thancross section of industries
2. studying the behavior/conduct of firms in the industry than industry concentration 
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Probably not.
Bain paradigm is based on the assumption that on the basis of market structure (concentration), we can infer the results of the suppliers on the market (use of monopoly power). In the opposite, supportersof the efficient market hypothesis (ESH)  hold the opposite direction of cause and effect. In their view, because the firms are very efficient (performance)they achieve the bigest market share. In this sense, the findings contradict Bain paradigm.
In contrast, the NEIO approach does not assume apriori  that suppliers on concentrated markets use power of monopoly, but tries to check by direct methods.
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I'm working on the measurement of organizational technical level in industrial environments. I would like to identify indicators from the logs of a management system. Does anyone worked on that topic?
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I suggest you looking at productivity engineering book by Prof. Sumanth. He introduced productivity cycle (Measurement, Evaluation, Planning and Improvement). From management systems view you can find the numerous skills for productivity improvement that each of them influence on related measures. Good luck.
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My goal is to propose a methodology to assess the economic and environmental impact of a new equipment/technology/production system in manufacturing or remanufacturing processes by using simulation and proper KPIs
I wonder:
  • what are the potentials and the shortcomings in using simulation (discrete event simulation particularly) for this kind of research goal
  • what are the alternative research methodologies (beyond that one above) to address this research goal.
I warmly embrace answers ranging from the sharing of experiences in this field to references, when clearly connected to the topic.
Thank you.
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Dear Ilaria,
It is very critical to determine some key performance indicators (KPIs) to track the changes. In this regard, you can do a literature review and find which factors are more critical for what you mentioned in your question (e.g. total production cost and cycle time for economic or CO2 footprint for environmental perspective). Following are some required steps:
1. Construct the current model and run it using the real data. Use KPIs as the model output (e.g. cycle time). Run the model for many times and check the report of KPIs.
2. Construct the new model, run it and check the same KPIs.
3. Compare the outputs. Is there any significant improvement?
4. Do a cost/benefit analysis. Can the achieved benefits justify the assigned costs?
5. Do a qualitative analysis (e.g. social perspectives) on the achieved benefits.
(Suggested software: Arena or ED)
You can check the following paper :
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After the articles by Peng & Illnitch '98, Peng '06 and Trabold '02 has there been more development on the research on intermediaries? E.g. when used by small to medium sized industrial firms, why they are still important in the times of the globalization and information and communication technology?
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Business intermediary is a living concept in business operation and research. It can be explored further in the Supply Chain Management research scope (in Operation Research), in Distribution Channel  in Marketing Strategy research, and in Sub-contracting or Outsourcing  concept in Operation Management Strategy research.
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How can we differentiate between natural factors and other economic factors that determine the price of lands? there are a plenty of factors that determine land price not in cities. it seems difficult to distinguish them or measure the effects of variables. I want to know some methodologies to find and measure these natural factors without including human factors such as distance to facilities or urban areas.
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location, richness of soil accessbility, water sustain capacity, water availability, slop rainfall climate etc are the major natural factors influencing farm land 
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Gas for MIG welding is one of major costs in fabrication.
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Similar to the previous answer there are several open literature guides (see below).  You may want to consider adaptive power supplies or dual wire feed units to minimize your overall cost.
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I am Md. Mizanur Rahman. Now i am working as a Senior Lecturer, Department of Business Administration, Metropolitan University, Sylhet, Bangladesh. My research interest areas are Management, HRM Issues. 
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I strongly agreed with the answers of Prof. Kamal Eddin Bani-Hani, Prof. Shibu.N.S. & Prof.John Hamer Powell.
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Business to Business applications usually deal with the logistics between the interested businesses. However, Supply Chain Management applications are playing a major role in fixing and managing that relation too, so are those application separate or integrated?
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Agree with both Tomascz and Mathias. Not sure I would concur with Frans. Why must SCM necessarily involve more than two business entities? It is conceivable that a firm is interested in only managing the link between itself and Tier 1 supplier or there are no further links in the chain (i.e., a single Tier). An SCM system is one kind of B2B system.