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Describes a spreadsheet approach for implementing Wagner‐Whitin (WW) and Silver‐Meal (SM) methods for lotsizing time‐varying demands. Suggests that this approach manages the computation and makes tedious and repetitive tasks more interesting; consequently, the student/user can concentrate on the concepts. Outlines the methods, which involve the computation of incremental costs (inventory carrying and replenishment costs) for several alternatives in each period. Presents a spreadsheet template to compute the incremental costs for possible alternatives which is created by using only a small number of spreadsheet formulae and a series of copy commands. The costs are displayed as a matrix. Describes a step‐by‐step procedure to determine the period and the quantity of replenishment.

Knowledge management (KM) is widely adopted by organisations to improve their performance and make informed decisions. Prior research has confirmed that Information Systems (IS) play a critical role in effective KM. The purpose of this study is to examine the existing literature on the role of cloud-based KM systems (C-KMS) in small- and medium-sized enterprise (SMEs) by understanding its impact on the five KM processes: knowledge acquisition, creation, storage, sharing and usage.

This study conducted a systematic literature review by examining 133 journal articles and 24 conference papers from 2010 to 2021 on the role of cloud computing in KM for SMEs.

This study revealed that there are numerous empirical analyses on KM processes and tools in SMEs; however, only few studies demonstrate how the whole gamut of KM processes can adopt cloud computing in SMEs. Therefore, SMEs are ineffective at KM with limited IS intervention. This paper offers a proposition on how C-KMS can impact all five KM process, thereby increasing its effectiveness of KM in SMEs. This study analysed the benefits of C-KMS that brings to SMEs in terms of availability, scalability, reliability, security and cost.

This systematic review is restricted to certain databases (ScienceDirect, Sage journals, Scopus and Emerald Insight) and specific IS conference proceedings to source articles. The selection of search criteria and time frame is based on this study’s assessment and choice. This study adds value to our understanding of the role of KM in SMEs, and it reinforces the role of cloud computing in effectively managing knowledge in SMEs. The proposal of C-KMS for the enhancement of KM has significant implications for SMEs to effectively use knowledge for their survival and superior performance.

This study suggests three practical implications. First, adopting and using C-KMS provide a strong foundation to manage knowledge for SMEs in a cost-effective way. Second, C-KMS improves the effectiveness of KM by increasing availability of knowledge artifacts, which in turn aids SMEs’ growth. Third, C-KMS is useful to codify SME’s knowledge, and accordingly supports employees to acquire and use knowledge based on their requirements.

This study discussed C-KMS with contemporary social issues, such as the COVID-19 pandemic challenges for SMEs and demonstrated how C-KMS can support SMEs to handle such crises by managing knowledge effectively.

This research highlights the importance of the implementation of a C-KMS for the enhancement of KM in SMEs. The review provides empirical evidence on the challenges faced by SMEs regarding KM, as they often only have enough resources to focus on a single KM process, predominantly knowledge sharing. Consequently, a holistic approach to KM cannot be realised by SMEs. In this context, the findings of this study offer theoretical and practical insights into the role of cloud computing by addressing the challenges of KM in SMEs.

Population ageing will bring economic challenges in the future. The purpose of this paper is to examine whether increased educational level could mitigate the consequences of population ageing on economic sustainability, measured as the gap between labour income and consumption.

Using the National Transfer Accounts (NTA) methodology, the authors decompose labour income and consumption by age and educational level (low, medium and high) and compare obtained age profiles with those calculated conventionally. In addition, using the population projections by age and educational level, the authors project both profiles to 2060 for selected EU countries and assess future economic sustainability.

The results show that the highly educated have a significantly higher surplus for a longer period then those with lower and medium education. Therefore, the improved educational level of individuals will have a substantially positive impact on labour income in the future—on average by about 32% by 2060 for all EU countries included. However, as the better educated also consume more, higher production does not fully translate into improved economic sustainability, but the resulting net effect is still positive at about 19%.

The authors present for the first time an NTA by education for 15 EU countries and show the importance of including education in the analysis of the economic life cycle. The authors also show that increased educational level will mitigate the consequences of population ageing on economic sustainability in the future.

The purpose of the research is to develop scientific and methodological recommendations for indicative evaluation and systemic management of the professional and qualification potential of the digital society and to approbate them by the example of modern Russia.

The authors use the proprietary algorithm of the creation and implementation of the professional and qualification potential of the digital society. Based on the new algorithm, a proprietary methodology of indicative evaluation of the professional and qualification potential of the digital society is developed.

The authors offer a complex of recommendations for systemic management of the professional and qualification potential of the digital society and their approbation by the example of Russia in 2020, which allow achieving high effectiveness of this management. The results of approbation of the proprietary methodology and recommendations by the example of Russia in 2020 showed that the professional and qualification potential of the digital society is rather high and well-balanced; it is normal but has perspectives for an increase. There is an imbalance, which is caused by the domination of the development of the education market over the market of labor and entrepreneurship. Based on this, managerial measures are recommended for the development of the professional and qualification potential of the digital society in Russia.

The offered algorithm sets the foundation of an expanded view of the studied process, according to which the professional and qualification potential of the digital society is not only limited by the educational market but also covers the labor market and entrepreneurship. This view is revolutionary for modern Russia. The advantages of the authors’ methodology of indicative evaluation of the professional and qualification potential of the digital society include the usage of the complete set of qualitative and quantitative indicators, delimitation of indicators as to the stages of the algorithm, and the improved matrix for treatment of the results.

This paper aims to present a panel data econometric model of the main determinants of house prices in the ten largest census metropolitan areas (CMA) in Ontario, Canada, for the years 2001, 2006 and 2011. The impact of immigration on the housing market in Canada is little researched; however, immigration plays an important role into the economy of Canada. According to Statistics Canada, not only is immigration key to Canada’s population growth but also without immigration, in the next 20 years, Canada’s population growth will be zero. The motivation for this study is the bursting of housing bubbles in some developed countries (e.g. USA). The authors analyze variables that are related to the immigration policy in Canada, accounting also for the impact of the interest rate, income, unemployment, household size and housing supply to analyze housing price determinants. The study investigates the magnitude of the impact of the top three leading categories of immigrants to Canada, namely, Chinese, Indian and Filipino, on the housing prices in Ontario’s largest cities. The results show the main factors that explain home prices over time that are interest rate, immigration, unemployment rate, household size and income. Over the 10-year period from 2001 to 2011, immigration grew by 400 per cent in Toronto CMA, the largest receiving area in Ontario, while the nonimmigrant population grew by 14 per cent. For Toronto CMA, immigrants, income, unemployment rate and interest rate explain the CA$158,875 average home price increase over the 2001-2011 time period. Out of this, the three categories of immigrants’ share of total home price increase is 54.57 per cent, with the corresponding interest rate share 58.60 per cent and income share 11.32 per cent of the total price growth. Unemployment rate contributes negatively to the housing price and its share of the total price increase is 24.49 per cent.

The framework for the empirical analysis applies the hedonic pricing model theory to housing sales prices for the ten largest CMAs in Ontario over the years 2001-2011. Following Akbari and Aydede (2012) and O’Meara (2015), market clearing in the housing market results in the housing price as a function of several housing attributes. The authors selected the housing attributes based on data availability for the Canadian Census years of 2001, 2006 and 2011 and the variables that have been most used in the literature. The model has the average housing prices as the dependent variable, and the independent variables are: immigrants per dwelling (Chinese, Indian, and Filipino), unemployment rate, average employment income, household size, housing supply and the interest rate. To capture the relative scarcity of dwellings, the independent variable immigrants per dwelling was used.

This study seems to suggest that one cause of high prices in Ontario is large inflows of immigrants together with low mortgage interest rate. The authors focused their attention on Toronto CMA, as it is the main destination of immigrants and comprises the largest cities, including Toronto, Mississauga, Brampton and Oakville. Looking over the 10-year period from 2001 to 2011, the authors can see the factors that impact the home prices in Toronto CMA: immigration, unemployment rate, household size, interest rate and income. Over the period of 10 years from 2001 to 2011, immigrants’ group from China, India and the Philippines account for CA$86,701 increase in the home price (54.57 per cent share of the total increase). Income accounts for CA$17,986 increase in the home price (11.32 per cent share); interest rate accounts for CA$93,103 of the average home price increase in Toronto CMA (58.60 per cent share); and unemployment rate accounts for CA$38,916 decrease in the Toronto average home prices (24.49 per cent share). Household size remain stable over time in Toronto (2.8 average household size) and does not have a contribution to home price change. All these four factors, interest rate, immigrants, unemployment rate and income, together explain CA$158,875 increase in home prices in Toronto CMA between 2001 and 2011.

The housing market price analysis may be more complex, and there may be factors impacting the housing prices extending beyond immigration, interest rate, income and household size. Finally, the results of this paper can be extended to include the most recent census data for the year 2016 to reflect more accurately the price situation in the housing market for Ontario cities.

The fact that currently, in 2017, the young working population cannot afford buying a property in the Toronto CMA area means there is a problem with this market and a corresponding decrease in the quality of life. According to The Globe and Mail (July 2017), a new pool in 2017 suggested that two in five Canadians believe housing in this country is not affordable for them. Further, 38 per cent of respondents who consider themselves middle or upper class believe in no affordability of housing. The Trudeau Government promised Canadians a national housing strategy for affordable housing. Designing a national housing strategy may be challenging because it has to account for the differential income ranges across regions. Municipal leaders are asking the government to prioritize repair and construct new affordable housing. Another reason discussed in the media of the unaffordability of housing in Toronto and Vancouver is foreign buyers. The Canadian Government recently implemented a tax measure on what it may seem the housing bubble problem: foreign buyers. Following Vancouver, in April 2017, Ontario Government imposed a 15 per cent tax on foreign buyers who are not Canadian citizens or permanent residents. This tax is levied on houses purchased in the area stretching from Niagara Region and Greater Toronto to Peterborough.

Few studies use Canadian data to explain house prices and analyze the effect of immigration on housing prices. There is not much research on the effect of the immigrants and immigrants’ ethnicity (e.g., Chinese, Indian and Filipino immigrants), on the housing prices in Canada cities. This study investigates the impact of the most prevalent immigrant races (e.g., from China, India and the Philippines) on housing prices, using data for Canadian major cities in Ontario within a panel data econometric framework. This paper fills this gap and contributes to the literature, which analyzes the determinants of housing prices based on a panel of cities in the Canadian province of Ontario.

The purpose of this paper is to evaluate the economic impacts of China’s hukou system and propose the possible direction for future reform.

The study develops a framework to incorporate the hukou system into the economic growth model. Using prefecture city-level panel data covering 241 cities over the period 2004–2016 and applying the fixed effects and instrumental variable regression techniques, the authors investigated empirically the impacts of the hukou system on city economic growth.

The study provides three main findings. First, the city sector conditionally benefits from labour mobility deregulation that allows migrants to work in cities. Second, the hukou system has different impacts on economic growth among cities with different sizes and administrative levels. Third, to offset the costs of providing exclusive public services to the migrants, the big or high-administrative-level cities can use their high-valued hukou to attract the high-skilled migrants, but the small- or low-administrative-level cities do not have this advantage.

This study suggests that the key for further hukou system reform is how to deal with the hukou–welfare binding relationship.

The authors developed a theoretical framework and conducted an empirical analysis on the direct relationship between the hukou system and economic growth to reveal the mechanism of how does the hukou system influence the city economic growth and answer the question of why is the hukou system reform so hard in China. The framework also sheds some lights on explaining the success and failure of the hukou system reforms in the past 40 years.

Libraries need to develop information processing systems for evaluation, budgeting, planning, and operations. Electronic spreadsheets lend themselves to a variety of applications, but are time‐consuming to create. A model template and macros that can be used in many different types of library data analysis have been developed here. The procedures demonstrated here can build an essential set of tools for meeting fundamental goals of administrative efficiency, effective use of library resources, staff motivation, and rational policy making.

The purpose of this paper is to investigate whether there is a causal impact of party affiliation of state governors operating within a liberal state legislature on labor market activity of transgender individuals. The common perception is that Republicans are more likely to believe a person’s gender is determined by their sex at birth than Democrats. Such beliefs can influence voting, policies and practices.

Survey data on employment outcomes and other individual level characteristics are used from two surveys focusing on transgender individuals for the periods 2008 and 2015. These surveys represent the largest collection of data that examines the experiences of transgender people in the USA. To establish a casual effect, this analysis employs fixed effects Ordinary Least Squares methods and Propensity Score Matching algorithms.

Exploiting variations in the party affiliation of governors and liberal state governments, the study finds mixed employment effects of living in a Democratic-governed liberal state. Specifically, this paper shows that transgender people living in such states have an 18 percentage point (or 26 percent) higher likelihood of being employed in the 2008 survey, but a 16.4 percentage point (or 25 percent) lower likelihood of being employed in the 2015 survey. Despite the lower propensity to be out of the labor market in the 2008 sample, results from both surveys indicate a higher likelihood of being unemployed. These findings are robust to the inclusion of additional covariates (including confounders), alternative specifications and different estimation techniques. Heterogeneous effects are also explored.

To the authors’ current knowledge, this is the first study to systematically investigate the relationship between living in democratically governed liberal states and labor market circumstances of transgender people in the USA. This is the first paper to establish a causal relationship using matching techniques. The paper also provides suggestive evidence of the role of government ideology in influencing the working lives of transgender people.

The purpose of this paper is to assess the role of local labour market conditions and pupil educational attainment as primary determinants of the post-compulsory schooling decision.

Through the specification of a nested logit model, the restrictive independence of irrelevant alternatives (IIA) assumption inherent in the multinomial logit (MNL) model is relaxed across multiple unordered outcomes.

The analysis shows that the factors influencing schooling decisions differ for males and females. For females, on average, the key drivers of the schooling decision are expected wage returns based on youth educational attainment, attitudes to school and parental aspirations, rather than local labour market conditions. For males, higher local unemployment rates encourage greater investment in education.

The contribution of this paper to the existing literature is threefold. First, a nested logit model is proposed as an alternative to a MNL. The former can formally incorporate the structured and sequential decision-making process that youths may engage with in relation to the post-compulsory schooling decision, as well as relaxing the restrictive IIA assumption inherent in the MNL across multiple unordered outcomes, an issue the authors discuss in more detail in the Methodology section below. Second, the analysis is based on extremely rich socio-economic data from the Longitudinal Study of Young People in England, matched to local labour market data and administrative data from the National Pupil Database and Pupil Level Annual School Census, which provide a broad set of unusually high-quality measures of prior attainment. The authors argue that such high-quality data and an appropriate model specification allows identification of the determinants of the post-compulsory decision in a more detailed manner than many previous analyses. Third, the data have the scale necessary to consider whether the determinants of post-compulsory schooling decisions vary by gender, a particularly important issue given the differential education participation rates of males and females (e.g. in this cohort, females are about 10 percentage points more likely to go on to higher education in the UK than males), and the gendered choices of occupation (see, e.g. Bertrand, 2011). The work will, therefore, provide recent empirical evidence from England on gender differences in the determinants of education choices.

To develop an understanding of communication among agribusiness journals and to examine patterns of citations that allow the measurement and description of the structure of communication flows among those journals in a network.

The data for this study were gathered from the Journal Citation Reports (JCR) published by Thomson Scientific (Philadelphia). The authors conducted a bibliometric analysis, based on an international trade analogy to explain the network of agribusiness journals and how these journals communicate with business and economics journals.

Business and economics journals and, particularly the traditionally major ones, surprisingly were scarcely every used. However, the British Food Journal stood out with 50 citations to marketing and strategic management journals.

There are predominantly four such limitations: only 33 journals were studied, only one 5-year time period was involved, that time period is a few years old and the journal characteristics were derived using data from the “Scopes” and “Information for Authors” text on the website of each journal.

Exchanges of agribusiness knowledge and information among diverse stakeholders (consumers, suppliers and public agencies) in a complex environment require a better understanding of the network of agribusiness journals and their relation to traditional business and economics journals.

Networks of journals facilitate cooperation and interactions to improve developments in the field.

Examining citations from and to the field of agribusiness is interesting and important because knowledge is transferred through networks comprise those who contribute to journals, read them and learn from them, i.e. by “talking” to each other as well as by practitioners who also read and learn from those journals.