A fuzzy goal programming approach to analyse sustainable development goals of India

Energy policy, environmental planning and economic development play a key role in sustainable development. Sustainable development requires suitable and strategic policies satisfying multiple and conflicting objectives. Fuzzy goal programming (FGP) is a well-known approach in multi-criteria decision-making for its practical application. In this article, a FGP approach is proposed to analyse environmental, energy and sustainability goals of India by the year 2030 with reference to the key economic sectors of India. The presented model analyses the improvement opportunities, requirement of efforts and implementation of the sustainable development plans. Numerical illustration is also provided for validation and application of the proposed model.     

From families to formal contracts: An approach to development

This paper develops a theory in which individuals can use one of two types of human/social capital to enforce contracts: “Local capital” relies on families and other personal networks; “market capital” relies on impersonal market institutions such as auditors and courts. Local capital is efficient when most trading is local, but only market capital can support trading between strangers that allows extensive division of labor and industrialization. We show that economies with a low cost of accumulating local capital (say, because people live close together) are richer than economies with a high cost of accumulation when long distance trade is difficult, but are slower to transition to impersonal market exchange (industrialize) when long distance trade becomes feasible. The model provides one way to understand why the wealthiest economies in 1600 AD, China, India, and the Islamic Middle East, industrialized more slowly than the West. We report an array of historical evidence documenting the pre-industrial importance of family and kinship networks in China, India, and the Islamic world compared to Europe, and the modernization problems linked to local capital.     

End-of-life care in nursing homes: the high cost of staff turnover

Nursing home staff turnover results in high cost--both economic and personal--and has a negative impact on the quality of care provided to residents at the end of life. Reducing staff turnover in nursing homes would benefit both the cost to the U.S. health care system, and, most importantly, the care residents receive in the vulnerable period leading to death. There is rising pressure on nursing homes to improve their palliative and end-of-life care practices and reduce transfers to hospital for situations and conditions that can be safely managed on site. Nursing care staff deserve an investment in the specific training necessary for them to give the highest quality care to dying residents. This training should be multifaceted and include the physiological, psychological, spiritual, interpersonal, and cultural (including ethnic) aspects of dying. Empowerment with these necessary knowledge, skills, and attitudes will not only result in better care for residents but likely also will reduce the burnout and frustration staff experience in caring for residents near death.     

Capacity planning in hospital nursing: a model for minimum staff calculation

An aging population, emerging technology, heightening patient expectations, rising health care costs, shorter patient stays, and growing pressure to improve quality have made the management of nursing resources even more critical today. While approaching a model for staffing levels, the authors considered factors such as patient acuity, work redesign, and minimum quality standards. The methodology for analysis included estimating the time needed to complete nursing tasks and calculating the average number of tasks per patient. With respect to nursing quality measures, the study examined the adequacy of nursing documentation including admission history, assessments, nursing procedures, and discharge report as well as nursing-driven outcomes such as fall and phlebitis rates. Lastly, the authors determined the theoretical number of staff needed to provide nursing care according to quality standards.     

A social contract approach to sustainability

This paper asks whether it is possible to derive a concern for future generations (“sustainability”) from an account of the firm as a social contract (SC) among its stakeholders. Two aspects of a leading SC model of the firm limit its usefulness for an analysis of sustainability. First, the stakeholders provide investments to the firm over time. Second, the relationship between contemporaries and future generations is marked by asymmetries of power and knowledge that need to be considered while reconstructing the SC today. I discuss three reformulations of the SC that are all, in principle, capable of introducing within the SC a concern for future generations. The first describes the contractors as heads of families. The second envisages a grand meeting of stakeholders of all generations. The third, which I find most defensible, views the SC as an ahistorical agreement reached behind a thick veil of ignorance. This agreement is based on John Rawls’s norm of reciprocity, whereby the stakeholders adopt today the decision they wish all previous (and future) generations had made regarding the rate of consumption of natural resources and emission of pollutants.     

A quantile approach to US GNP

In this paper we fitted a quantile self-exciting threshold autoregressive (QSETAR) time series model to the growth rate of real US GNP. We also presented a forecasting method for QSETAR models. This forecasting method makes it possible to obtain the predictive quantiles and predictive distribution function of x_t+m given x_t for m > 0, and hence any quantities of interest can be derived. Therefore, this new approach allows us to study the US GNP from a distribution point view, rather than from a mean point of view. The results obtained in this paper show that the method works very well in practice.     

A compatibility approach to scenario evaluation

This article presents a novel approach for evaluating scenarios that represent combinations of a given set of possible events. The approach utilizes compatibility assessment, a heuristic method for inferring relative compatibilities of different scenario combinations. An illustration of its application is taken from a technology assessment study prepared for the National Science Foundation.     

A signaling approach to soft budgets

A new explanation for soft budget constraints is given. Projects of an agent are often the more profitable, the more confident the agent is in the principal's competence and/or supports. Principals can signal support and/or competence through a soft budget constraint.     

A risk-driven approach to exchange rate modelling

The paper presents a new approach to exchange rate modelling that augments the CHEER model with a sovereign credit default risk as perceived by financial investors making their decisions. In the cointegrated VAR system with nine variables comprised of the short- and long-term interest rates in Poland and the euro area, inflation rates, CDS indices and the zloty/euro exchange rate, four long-run relationships were found. Two of them link term spreads with inflation rates, the third one describes the exchange rate and the fourth one explains the inflation rate in Poland. Transmission of shocks was analysed by common stochastic trends. The estimation results were used to calculate the zloty/euro equilibrium exchange rate.     

A new approach to modelling sigmoidal curves

Growth and diffusion phenomena have become of great interest to investigators in many disciplines, such as Biology, Demography, Economy, Agriculture, etc. These processes are generally analyzed by means of growth curves. As, in nature, it is not possible for any variable to continue growing indefinitely, we can consider any growth process to have an upper limit or saturation level. Thus, should a model represent a growth phenomenon, it will be described by a sigmoidal or S-shaped curve. There are a wide variety of growth models in general and specific literature. Of these, the logistic model is without doubt one of the most studied in practice, as well as some modifications of it, including recent investigations directed to the decomposition of a growth curve into various logistic components [Technol. Forecast. Soc. Change 47 (1994) 89; Technol. Forecast. Soc. Change 61 (1999) 247.]. In all the cases above, the adopted approach includes fitting the trend curve to the data by means of a well-known estimation procedure, such as least squares. We suggest a somewhat different approach, which consists of expressing the model through its differential equation and searching for a functional specification for the variable representing growth rate. Two series have been chosen from the recent literature in order to illustrate the methodology presented.     

A cardinal approach to straightforward probabilistic mechanisms

In every probabilistic mechanism, society selects an alternative, through a random device, out of a subset of indifferent alternatives. Consequently, in this context individuals face uncertainty and value the different lotteries on alternatives by their expected utility, so that they make use of a Von Neumann-Morgenstern cardinal utility function. Surprisingly, the social choice approach to probabilistic mechanisms assumes the use of ballots which preclude the complete expression of behaviour towards risk: individuals can only announce their ordinal preferences, or an approximation of their cardinal preferences, since in any case only a finite number of representations of preferences is available. This paper attempts to study voting systems in which individuals can express the cardinality of their preferences by assigning weights to the alternatives. It is shown that by voting with ballots which reflect weighting a new class of straightforward probabilistic mechanisms is defined, and that this class strictly contains the class of probabilistic straightforward mechanism designed by Gibbard.     

A new approach to testing unemployment hysteresis

This paper proposes a novel approach to testing unemployment hysteresis. It examined the existence of hysteresis in the unemployment rates of four Nordic countries, namely Denmark, Finland, Norway and Sweden, for the period of 2000–2014. The study applied four alternative methods to analyse the data. The best estimation procedure was chosen in a simple and consistent way. As the findings indicated, the ADF test and FADF test failed to reject the null hypothesis of unemployment hysteresis in all four countries. The ADF–SB test produced mixed results: it rejected the null hypothesis of hysteresis for Denmark and Norway, but failed to reject the null hypothesis for Finland and Sweden. The FADF–SB test yielded more consistent findings: it rejected the null hypothesis for all four countries. Furthermore, findings from the F-tests clearly indicated that the FADF–SB test was the best method among the four proposed alternatives. Despite some discrepancies the findings of this study suggest that unemployment in the four Nordic countries had a mean reversion tendency.     

A hedonic-output-index-based approach to modeling polluting technologies

Despite some recent criticisms, the conventional radial distance function, which treats undesirable by-products as either frontier shifters or inputs, remains a popular go-to formulation of polluting production processes among practitioners. This unfading popularity is arguably driven by the ability of radial distance functions, unlike alternative directional distance functions, to allow for unit-free multiplicative changes in arguments as well as, by implicitly postulating the radial direction, to free researchers from the dilemma of having to explicitly choose the directional vector. In this paper, we offer a generalization of the standard radial distance function to polluting technologies that can accommodate undesirable by-products in a more economically meaningful way. Specifically, we propose modeling undesirable outputs via a hedonic output index, which is meant to ensure that pollutants are treated as outputs, as opposed to inputs or theoretically unregulated frontier shifters, while also recognizing their undesirable nature. By using a radial input distance function generalized to encompass an (unobservable) hedonic output index of desirable and undesirable outputs, we are able to meaningfully describe relationships between different products (including the complementarity of desirable and undesirable outputs) within producible output sets as well as to represent technically feasible polluting production possibilities given inputs. An empirical application of our methodology to the case of Dutch dairy farms in 2001–2009 demonstrates the complexity of interactions between outputs, thereby attesting to the value of more elaborate representations of production possibilities.     

A time series approach to g convergence

This paper applies time series analysis to study how the gap between a number of countries and the USA evolves through time. As other authors, it is found that time series analysis provides a better insight into the concept of convergence than the cross sectional one. The econometric results show that the stochastic behaviour of the output disparity varies considerably: neither the steady-state equilibrium nor the speed of convergence are unique and constant across countries and time. In general, there is catching up for European countries, convergence for East and South Asian countries, and neither of them for Latin American countries.     

An analytic network process approach to partner selection for acquisition and development

To cope with rapid technological change and the increasing R&D costs during a period of decreasing technology and product life cycles, acquisition and development (A&D) has been suggested to be an important method for high-tech firms to achieve higher economic returns. However, few studies have examined the operational problems of choosing a compatible A&D candidate from a pool of potential A&D candidates. To address this limitation, this study proposes an approach based on the analytic network process (ANP) to rank a set of potential A&D candidates within a multivariate set of attributes systematically. A total of 25 criteria were identified and used to construct the ANP model in which the final selection is based on the resulting priorities assigned to the A&D candidates. A case study of a semiconductor manufacturing company was conducted to illustrate the application of the proposed approach. The results indicated that the proposed ANP method can aid in A&D decision-making problems systematically.     

A panel cointegration approach to the investment-saving correlation

This paper augments the empirical literature concerning the Feldstein-Horioka puzzle using non-stationary panel data. Recently developed tests for panel cointegration and panel unit root tests are employed. We find substantial evidence to support the hypothesis of no cointegration in this panel, implying a high degree of international capital mobility. Our results suggest that tests for cointegration in panel data provides a better methodological focus than the magnitude of saving-retention coefficients. First version received: August 1999/Final version accepted: December 2000