Science topics: Industrial OrganizationProductivity Analysis
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Productivity Analysis - Science topic
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Questions related to Productivity Analysis
Let's collect the generative AI productivity booster solutions per category. Let me know what you think, your options, or suggestions.
AI Bot
- ChatGPT https://chat.openai.com/
- Llama2 https://ai.meta.com/llama/
- Perplexity https://www.perplexity.ai/
- Copilot https://lnkd.in/gH6YWbc5
HR
- Teamtailor https://lnkd.in/e6pT3hYV
- Faltah https://lnkd.in/dhqRfPC4
- EdApp https://www.edapp.com/
- IntelliHR https://intellihr.com/
CODING
- GitHub Copilot https://lnkd.in/dWK26VKK
- Codeium https://codeium.com/
- Askcodi https://www.askcodi.com/
- Tabnine https://www.tabnine.com/
CREATIVITY
- Runway https://runwayml.com/
- Beautiful.ai https://www.beautiful.ai/
- Midjourney https://lnkd.in/dbn_w7XH
- Dalle2 https://lnkd.in/dW5j4GtY
MARKETING
- Headlime https://headlime.com/
- AdCreative https://www.adcreative.ai/
- Rytr https://rytr.me/
- Looka https://looka.com/
WRITING
- Grammarly https://www.grammarly.com/
- Copy.ai https://www.copy.ai/
- Jasper AI https://www.jasper.ai/
- Wordtune https://www.wordtune.com/
PRODUCTIVITY
- Taskade https://www.taskade.com/
- Mem https://get.mem.ai/
- Notion https://lnkd.in/dYcWW9Ke
- Decktopus https://www.decktopus.com/
I am performing a Stochastic Frontier Analysis on unbalanced panel data in R with the package frontier (based on Battese & Coelli 95). I wonder how can we check for autocorrelation / endogeneity. The residuals() function returns the residuals, which consist of both the noise term and the inefficiency term, i.e. residual = y - f(x) = v - u. I am not sure if one can use these residuals to test for heteroscedasticity (Breush-Pagan test) or autocorrelation (LM test). Have you seen this in the literature?
A Latin American company has National and International projects. National ones have high productivity (in terms of hours spent and hours billed to the customer), but the profit is low (compared to the International projects) because the incomes and the costs of the projects are in Pesos (a weak currency). On the other hand, the International projects have a productivity of around 60%, but since the incomes are in Dollars and the costs are in Pesos, they are highly profitable, even though they are not productive.
This has bias the perception and had led the company to believe that the 60% of productivity is fine because the profit is enough. On the other hand, is very difficult to compare one type of project with the other.
How would you recommend to assess the cost-benefit analysis in an agnostic point of view, that make both types of projects comparable?
I know that using non-discretionary input could be an issue in the original, input-oriented DEA models where input can be expanded and/or contracted. The concern, I think, was that we don't want to produce efficiency scores suggesting efficiency could be improved by reducing uncontrollable (non-discretionary) inputs. However, I wonder if the inclusion of non-discretionary input is as consequential for output-oriented VRS DEA models? Most of the literature is based on input-oriented DEAs. Any comments will be appreciated, Thanks.
I have got the time series data (results) of mi, tc, pech and sech. How to elucidate these? How to correlate these with real world meanings?
The focus of this discussion is software for Football. According Chang (2018), mentioning Carling (2005), generally, performance analysis can be classified into two main categories: notational analysis and motion analysis. The two systems have different focuses. Notational analysis provides factual record about the position of the ball, the players involved, the action concerned, the time and the outcome of the activity, etc. Motion analysis focuses on raw features of an individual’s activity and movement, for example, identifying fatigue and measuring of work rate.
The two systems contribute for the performance analysis which has three main aims:
- Observing one’s own team’s performance to identify strengths and weakness
- Analysing opposition performance by using data and trying to counter opposing strengths and exploit weaknesses
- To evaluate whether a training programme has been effective in improving match performance
Performance analysis is not just about analysing matches and games. It is essential in the training programme to help coaches improve players’ performance. The following figure shows the coaching cycle. Performance analysis plays a key role in this cycle. Starting from the top, “Performance” means the performance in the game or training. “Observation” can be from the coach or video camera. Since research indicates that coaches are able to recall fewer than half of the key incidents that arise during the game, video camera is a better way which can record all the key events (actions and movements) for further analysis. In “Analysis”, it means analysis of data which include data management. For example, using performance analysis software to code the game, editing footages from the camera, extraction of data from data provider, etc. These are the areas in which the performance analyst spent most of the time. The product of this “analysis” stage can be statistical analysis and video recordings. In “Interpretation”, it can be put in two ways according to my experience. It could be done by coach or performance analyst. Some analysts have the authorisation from coach to interpret the data and then write a report or make a presentation to the coach or team. Some coaches just want the data from performance analysts and the coaches will interpret the data by themselves. It really depends on the coaches’ preference and the partnership between the analyst and the coach. After that, “planning” means the coach plan what to do after knowing what went wrong or which part the team did well. The coaches have to evaluate the performance prior to this planning stage. Otherwise, he doesn’t know how to improve the team’s performance in the next match. In most of the cases, it means the planning of the coaching session using the result of the performance analysis. “Preparation” means the execution of those coaching session in the training so prepare the team for the coming game. It will go back to the “Performance” stage and the whole cycle keep going.
What kind of Software or App are you using for Performance Analysis in football? Can you share with us the positives and negatives aspects according your experience?





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I've already estimated the technical efficiency model, technical inefficiency effects model, and got the values of log likelihood, σ2, γ, and I just want to test the hypotheses concerning the model parameters.
Attached is an example of a table containing the results of a stochastic frontier model (Cobb-Douglas production function), in addition to the results of the technical inefficiency effects model (10 business environment variables (Zi)). Could you please, given the estimated parameters in table (1) tell me how to test the following hypothesis:
1. Cobb-Douglas does not the appropriate production function form
(H0: β3 = β4 = β5 = 0)
2. No Technical inefficiency effects
(H0: γ = δ1 = δ2 = …= δ10 = 0)
3. No stochastic inefficiency
(H0: γ = 0)
4. No joint inefficiency variables
(H0: δ1 = δ2 = …= δ10 = 0)
Thank you very much in advance for this valuable help.
Dear collegues, researchers and practicioners on DEA.
In the 16th International Conference on Data Envelopment Analysis we presented deaR, a new R package for DEA. Now, it is a pleasure for me to announce that deaR is available to be installed and used.
deaR has been designed and built so that non-R users can easily use it. This package allows to run a wide variety of models based on DEA:
- Conventional DEA models: CCR, BCC, directional distance function multiplier, additive, non radial, sbm, radial super efficiency, additive super efficiency, sbm super efficiency, cross efficiency, bootstrapping, etc.
- Malmquist index
- Fuzzy DEA models: Kao and Liu´s model, some possibilistic DEA models, fuzzy cross efficiency.
You can get a brief introduction tutorial to install and use deaR (in English, Spanish, and Chinese) by clicking on the following link:
deaR is not only oriented to research but also teaching. For that reason, deaR provides some datasets that come from articles already published. These datasets are used in the deaR function examples to replicate the results of the articles.
We would really appreciate if you could spread the information about deaR among your colleagues and students.
We will release a deaR shiny version (an interactive web app) son. We will inform you when it is available.
Any comments and suggestions to improve deaR will be really appreciated. We also accept suggestions of DEA models to be considered for being programmed in new versions of deaR.
Best regards.
A Primary Author Citation Index (PACI) or p-index, proposed here, would not count citations of published works by scientists, but would instead determine the proportion (percentage) of all published works [with at least 1 citation] by a scientist for which the scientist is senior (first) author on the publication, regardless of the number of authors on each individual publication (included in the p-index calculation). The intended primary purpose of the p-index is to determine the proportion of a scientist's career publications that the scientist actually contributed to writing the majority portion of the publication (for which the first or primary author is most responsible and credited). The p-index value attempts to quantify a scientist's career accomplishments in terms of completing the entire research cycle, culminating with the actual primary (substantial) writing of all final research and related products (study results and other types of publications). Please do not respond by addressing the many problems associated with undue credit given to scientists in positions of power (over subordinate scientists) or different conventions, policies, or ethics used in determining authorship order (such as which scientists got the grant, did most of the research, or collected most of the data presented in a paper); and please refrain from giving unconstructive opinions.
Some studies have found managerial quality to be significantly associated with employee productivity and firm performance (Cirera & Maloney 2017 Innovation Paradox; Haldane 2017 Productivity puzzle; Bloom Sadun & van Reenen 2016 Management as technology). Yet despite these findings, there has been no apparent elevation of this factor in the intervention and treatment of poor productivity organisational environments. The question becomes; why is this so ? Why is the message not getting translated into practice? Is there a need for a wider and richer set of empirical evidence to prove the significance ? Are there strategies to catalyse the process of transformation?
Hello. I was reading a literature on the estimation of a (firm-level) production function.
y = a0 + a1x + e
where e is an error
To avoid the endogeneity issue, I found that the econometricians divide the error term into one which is observable by the firm, but not by the econometrician (u) and the other i.i.d error term not observable by both (v) as below
y = a0 + a1x + u + v
Then, they control for 'u' using a proxy (because it is the source of endogeneity). My questions is that, after obtaining consistent estimates for a0 and a1, they use the residual `u_hat' as the measure of the level of TFP as
TFP = u_hat = y - a0_hat - a1_hat * x
However, isn't it true that the above TFP also contains v_hat such that
TFP = u_hat + v_hat = a0_hat - a1_hat *x?
Is there any particular reason that the current literature use the former and dismiss v_hat?
Thank you so much in advance!
We work on dates and we need to do volatile product analysis on top, and we do not have head space nor spme,
And we were not able to make extractions by traditional methods, then, what are the appropriate solvents and what are the effective methods for making these extractions?
I am trying to build a Panel data for Norwegian oil companies to analyse their productivity as a function of Capital, Labour and R&D expenses. I was only able to find relevant data on 5 companies where in the industry there are 60 licensed to operate, the sample is indicative of around 10% population. 2 companies are industry leaders. remainder are med/small sized. For capital, I shall be using change in logs of market cap over the year. For Labour, change in logs of number of permanent employees. I am converting all the values to 2016 USD equivalent to account for inflation.
VA = Sales - Intermediate purchases
DlnVA = a*DlnK+b*DlnL+c*(realR&Dspend/realVA)
The issues I am facing-
1)I am stuck trying to take DlnK for the respective values. If you could show mw how to take those it'd solve a major problem for me. I want to know whether to use market capitalisation or values of Total assets - Current Liab from the balancesheets and then discount them accordingly for measuring K. Please note, K will exclude all R&D investments.
2) What kind of errors/problems I might face comparing companies like Statoil (International Oil Comp) and Petoro (Local Norwegian Comp) on the basis of the R&D exp which might not have necessarily been carried out in Norway itself.
How can productivity be measured for a generic pharmaceutical company?
I have two questions. If anybody helps me, I shall be highly obliged. Thanks in advance.
(i) Can anybody provide me the generalized primal version (i.e. maximization problem) of input-oriented VRS model?
I have tried it myself with an example. Actually, I tried to convert an input-oriented VRS model from dual version (i.e. minimization problem) to primal version (i.e. maximization problem). I found in case of objective function and constraints, an additional variable will come that does not exist in case of CRS model primal form (maximization problem). Additionally, the denominator part that is equal to 1 (constraint) in CRS primal form, it becomes less than or equal to 1 in VRS primal form. Am I right?
(ii) I know that in input-oriented VRS model, pure technical efficiency is calculated, scale efficiency is eliminated. I also know that in dual form it is done by adding a constraint summation of lambda or dual weights is equal to 1. However, I cannot relate these things.
Additionally, how this (i.e. pure technical efficiency without scale efficiency) can be explained with the primal form of VRS model?
Any kind of suggestion will help me a lot.
I'm able to perform the discrete version with summations, but am having a hard time doing it with integrals. In my case firm TFP has a continuous distribution and shares are a function of productivity as well.
does anyone know articles who talks about cognitive, affective and personality correlates
To choose between group-based incentive programmes or individual based incentive plan
Day today life products small to big
I've found EWPS, but it is designed for subjects with/without mental disorders.I'm looking for an instrument to be used in a self-report format. Anyone have ideas?
Would expanding the levels of flexibility for movements of talent between firms and within firms result in a positive productivity impact (refer section 1, page 5 on Policy Document attached). On a scale of Very Low, Low, Neither Low nor High, High, Very High, what productivity impact would most likely be the result ? Are there empirical data to support your assertion ?
Policy perspectives aimed in favour of unshackling SME’s of unnecessary strictures and empowering SME's to achieve talent-driven, outwardly-focused global competitiveness should feature flexibility to respond to market dynamism.
Flexibility covers a wide range of issues including:
a) Labour force training should be flexible in its delivery and not be rigidly tied to historical sectors and industries. Training content and packages should rather be dynamically adjustable and malleable to suit emergence of new sectors and industries. Responsive repackaging should be a key feature
b) The picking of winners and locking in / redirecting training resources to those ends is to be discouraged. The identification of areas of comparative advantage and repurposing training resources to those ends is also to be discouraged. Preference is for flexibility to be able to match market demands. Where appropriate, then time-limited Tax Incentives may be dynamically deployed to encourage training in emergent new sectors. However, there is a danger of having these incentives becoming institutionalised and remaining on the books way past their useful and value-enhancing period. Constant policy and legislative re-calibration would therefore be required.
c) Certification and training of the labour force should seek to produce an outcome where human talent is flexible and have the trained / certified individual be imbued with the capacity and capability to respond in a dynamic way to the varying job opportunities that will emerge over their lifelong working cycle.
d) Hire and Fire practices should be reviewed to eliminate rigidity and so adjusted to build in higher levels of flexibility in order to
(1) allow for easy and smooth movement of talent dynamically between firms and sectors, reducing stickiness and enhancing responsiveness as market demands change;
(2) allow for smooth movement within firms. As staff transition through their individual life cycles, job cycles and task cycles, Personal Productivity Performance changes and impacts their work output.; in some cases, upwardly and in some cases, downwardly. As individuals yearn for differing work-life balance states, then the SME firm needs an ability to flexibly treat with these employee desires in order to retain talent, or attract talent. Both individuals and firms need the capability and flexibility to adjust the form of engagement in order to align to these changing conditions. Where, on the other hand, the firm faces declines due to market conditions they will need flexibility to change talent engagement from one form to another (eg from flat-fee compensation base to a performance-fee base). Further, as the skillset of the talent becomes mismatched with market needs, then flexibility will be needed to enable enhanced responsiveness through training and development but also through job and task modifications. Rules for engagement, disengagement and modification of engagement would need to support innovativeness, productivity and competitiveness.
Technical Report Priority policy recommendations for transforming individual ...
Is there a positive benefit to aligning compensation systems to firm productivity ? (refer section 3, page 8 on Policy Document attached). On a scale of Very Low, Low, Neither Low nor High, High, Very High, what productivity impact would most likely be the result ?
Are there empirical data to support your assertion ?
Technical Report Priority policy recommendations for transforming individual ...
Regarding Positive and Negative Spillover in Work Life Blance
I have reviewed various theories like social capital, connectivism, metcalfe's law, already but they don't seem to capture the essence of my study.
Dear researchers
I'm evaluating the effects of mobbing on organizational productivity, and I want to know whether there are any researches about this topic? especially quantitative ones.
I would like to thank you in advance for your answers.Best Regards
There are many studies found in the literature regarding influence of organization culture on the productivity of employees. Can anyone give me some insight on the reverse fact (i.e., influence of productive employees on organization culture) ?
I try to assess team-level proactive traits (not behaviors). Can anyone suggest a good measure or source to develop a good measure?
or anyone can suggest a good measure for team proactive climate?
What are the main and other efficient and developed methods as ANN or Multiple regression analysis that can be used on measuring the Climate and Geography factor influences to the construction company productivity by regions ? I am looking for suitable and flexible methods that can be used on my research work. I am going to publish SCI Journals asap and looking for benefit modeling tools or methods. ...
I am looking for any kind of measurement of KPI´s related with productivity in an environment of business intelligence, specially manufacturer.
I would like to assess the productivity change across a 72 DMUs over a 5 year period in a health system. I have 2 inputs and 3 outputs.
Yearly partial productivity of capital of a company is to be calculated.
The critical positive measure of productivity in the government sector is the improvement in the ratio of the output of the public service to the costs for the delivery of that service; the higher the ratio the better the productivity. How does one compare the productivity of the government service delivery in one jurisdiction against the productivity of another ? Does a global index exist for reporting on this type of comparison ?
I am currently working on Project Management in Indian Pharmaceutical Industry and through my study would like to show that project management helps in improving productivity of an organization.
I am interested to estimate technical efficiency based on Battese and Coelli (1992) model. I have tried many times for the estimation both using the command prompt as well the use of instruction file in Frontier 4.1. But the dialog box immediately disappear once I end up the process by giving the command through running the FR0NT41 .EXE. Could anyone guide me where is the problem and how could i estimate it.
I am keenly interested in what the parameters classified as input and output factors/ variables that could be used to measure performances/productivities of exploration and production activities in oil and gas sectors. Where can I find similar research irrespective of the methodology or method deployed?
Hello. I performed ROS production analysis on A549 cells exposed to nanoparticles, I know that primary mechanism to be investigated for NP toxicity is the ROS production or oxidation stress and many papers co-relate this analysis. In my experiments the cell viability decreases to 25% or lesser. Does the co-relation exist still? The cell death would cause the DCF to leak out and there are not enough cells for the conversion of DCFDA to DCF for long exposure times. What do you all think about this? I need feedback
Thank you
Some researchers stay at their labs until midnight or maybe later. Some of these people enforce their students to do so, but I see that none of them produce more than other people who leave their labs on time.
What makes me post this question is the picture that I've attached with the question. It mainly talks about working in industry, but in my opinion it could be applied to researchers in their labs as well, couldn't it?
I totally agree with this, what do you think? Please tel me if I am wrong and these instructions are not associated with researchers.

A formate ion of some concentration is present in initially known concentration of naOH
I would like to know what parameters to use in establishing the efficiency of exploration and production activities in oil and gas organization
The difference between efficiency and effectiveness is that efficiency refers to doing things right, while effectiveness refers to doing the right thing. Efficiency focuses on the means, while effectiveness focuses on the end result. Moreover, efficiency is short term i.e. current state, while effectiveness is long term.
In the question below, Carlos Alberto asked about the meaning of productivity. Can we use the ideas of productivity for tangible goods also for intangible results as in science and academia? Could it help heal the many problems our community has with impact, impact engineering and abuse of different related indices?
Productivity analysis is a new approach to evaluate technologies in production processes at the micro level, we use the stochastic frontier approach to the analysis and macro economic development of countries use Malmquist indices. Generally, policy makers use a piecemeal approach and confuse productivity with yields.
I am more interested in what is considered "real effort" (not abstract effort), whether from cognitively taxing tasks (e.g. on working memory) or from phsyiologically taxing tasks. Both forms of effort are often experience as "fatiguing" or "exhausting".
As productivity is the ratio of output/input, can we use both output and input as predictor variable and productivity as response variable to form regression equation?