Comparative Analysis of Text Data in Successful Face-to-Face and Electronic Negotiations

Various combination of Natural Language Processing and Machine Learning methods offer ample opportunities wherever texts are an important element of an application or a research area. Such methods discover patterns and regularities in the data, seek generalization and in effect learn new knowledge. We have employed such methods in learning from a large amount of textual data. Our application is electronic negotiations. The genre of texts found in electronic negotiations may seem limited. It is an important research question whether our methods and findings apply equally well to texts that come from face-to-face negotiations. In order to confirm such more general applicability, we have analyzed comparable collections of texts from electronic and face-to-face negotiations. We present our findings on the extent of similarity between these two related but distinct genres. In this study we have analyzed similarities in the text data of electronic and face-to-face negotiations. The results show that – in certain conditions – vocabulary richness, language complexity and text predictability are similar.This is an expanded version of a paper published in the Proceedings of FINEXIN 2005 (Workshop on the Analysis of Formal and Informal Information Exchange during Negotiations), 31–42, Ottawa, Canada, May 2005.     

Managing retailer profitability—one customer at a time!

This study examines how customer lifetime value (CLV) can be computed at individual customer level in a retail setting to maximize profitability. The study finds that maximum positive impact to CLV occurs when the customer cross-purchases, shows multi-channel shopping behavior, stays longer with the firm, buys specific product categories and purchases more frequently with the firm. Interestingly, the CLV follows an inverted U relationship with increase in return of prior purchases. Other interesting findings include a surprisingly low correlation between customer loyalty and future profitability and low correlation between stores’ historic revenues and future profitability. Several implications are suggested for retailers to manage and maximize customer profitability as well as store profitability.     

The association of pain interference and opioid use with healthcare utilization and costs,and wage loss among adults with osteoarthritis in the United States

Abstract

Aim: To examine associations of opioid use and pain interference with activities (PIA), healthcare resource utilization (HRU) and costs, and wage loss in noninstitutionalized adults with osteoarthritis in the United States (US).

Methods: Adults with osteoarthritis identified from the Medical Expenditure Panel Survey for 2011/2013/2015 were stratified by no-opioid use with no/mild PIA, no-opioid use with moderate/severe PIA, opioid use with no/mild PIA, and opioid use with moderate/severe PIA. Outcomes included annualized total HRU, direct healthcare costs, and wage loss. Multivariable regression analyses were used for comparisons versus no-opioid use with no/mild PIA (referent). The counterfactual recycled prediction method estimated incremental costs. Results reflect weighted nationally representative data.

Results: Of 4,921 participants (weighted n?=?20,785,007), 46.5% had no-opioid use with no/mild PIA; 23.2% had no-opioid use with moderate/severe PIA; 9.6% had opioid use with no/mild PIA; and 20.7% had opioid use with moderate/severe PIA. Moderate/severe PIA and/or opioid use were associated with significantly higher HRU and associated costs, and wage loss. Relative to adults with no/mild PIA, opioid users with moderate/severe PIA were more likely to have hospitalizations, specialist visits, and emergency room visits (all p?<?.001). Relative to the referent, opioid use with no/mild PIA had higher per-patient incremental annual total healthcare costs ($11,672, 95% confidence interval [CI]?=?$11,435–$11,909) and wage loss ($1,395, 95% CI?=?$1,376–$1,414) as did opioid use with moderate/severe PIA ($13,595, 95% CI?=?$13,319–$13,871; and $2,331, 95% CI?=?$2,298–$2,363) (all p?<?.001). Compared with the referent, estimated excess national total healthcare costs/lost wages were $23.3 billion/$1.3 billion for opioid use with no/mild PIA, and $58.5 billion/$2.2 billion for opioid use with moderate/severe PIA.

Limitations: Unobservable/unmeasured factors that could not be accounted for.

Conclusions: Opioid use with moderate/severe PIA had significantly higher HRU, costs, and wage loss; opioid use was more relevant than PIA to the economic burden. These results suggest unmet needs for alternative pain management strategies.     

Navigating the Impact of Globalization on Bank Efficiency in China

The paper provides for the first time empirical evidence on the impact of economic globalization on bank efficiency in a developing economy. Using the data envelopment analysis method, we compute the efficiency of the Chinese banking sector during 2000–2007. The empirical findings suggest that the inefficiency of the Chinese banking sector stems largely from scale rather than pure technical inefficiencies. Examining different components of economic globalization, we find that greater economic integration through higher trade flows, cultural proximity and political globalization have significant and positive influence on bank efficiency levels. The empirical findings suggest that liberalization (restrictions) of the capital account exerts a negative (positive) influence on bank efficiency levels in China.     

Do men and women really shop differently? An exploration of gender differences in mall shopping in India

‘Men Buy and Women Shop’ proclaims a new Wharton Research on shopping habits of the American consumer (2007). There is found to be considerable difference in the way men and women shop in the West. Is this true across cultures? Indian retailing is generating considerable interest within the country and abroad. India has been rated as the fifth most attractive emerging retail market and was ranked first in a Global Retail Development Index of 30 developing countries drawn up by A T Kearney. Organized retail, best represented by the mushrooming malls, has come to play a defining role in building and supporting this veritable base of retail consumers. Therefore, it is of utmost interest to retailers and academia alike to understand the consumer dynamics behind the newly evolving consumption culture. This study explores mall‐shopping habits in India and attempts to identify and contrast possible differences between genders using a sample of 2721 mall consumers across seven cities. While the findings suggest that in India there are significant differences in shopping behaviour that can be ascribed to gender, there are fundamental questions about stereotyping of shopping as a feminine activity. To do this, discriminant analysis has been used to study whether shopping orientation and mall‐shopping attitudes can discriminate between male and female shoppers.     

Demand-side factors in optimal land conservation choice

The dominant paradigm of conservation-reserve planning in economics is to optimize the provision of physical conservation benefits given a budget constraint, implicitly assuming the value of biodiversity and ecosystem function is not affected by human proximity to that natural capital. There is evidence, however, that human willingness to pay (WTP) for conservation declines with distance—a phenomenon we call “spatial value decay”. This paper begins a new strand of the conservation planning literature that takes demand-side factors – location of people in the landscape, the degree to which WTP for conservation depends on proximity – into account. We use theoretical models of linear abstract landscapes to explore the impact of demand-side factors on two facets of conservation choices: siting of a single reserve when conservation potential is greatest near a critical site, and siting of multiple reserves when fragmentation reduces physical conservation services produced. Our results show how planners should sometimes employ increased fragmentation to capture value when people's preferences are not very highly localized, and how optimal policy balances proximity to the ecologically critical site with proximity to people. In some scenarios, the payoff to using a reserve design approach that considers demand-side factors is large, but we find that spatial value decay reduces the benefits that can be gained from any conservation-planning approach.     

A comment on Mendeş and Yiğit (2013), ‘Type I error and test power of different tests for testing interaction effects in factorial experiments’, Statistica Neerlandica, 67:1–26

In their advocacy of the rank‐transformation (RT) technique for analysis of data from factorial designs, Mende? and Yi?it (Statistica Neerlandica, 67, 2013, 1–26) missed important analytical studies identifying the statistical shortcomings of the RT technique, the recommendation that the RT technique not be used, and important advances that have been made for properly analyzing data in a non‐parametric setting. Applied data analysts are at risk of being misled by Mende? and Yi?it, when statistically sound techniques are available for the proper non‐parametric analysis of data from factorial designs. The appropriate methods express hypotheses in terms of normalized distribution functions, and the test statistics account for variance heterogeneity.     

Price expectations of sheep and goats by producers and intermediaries in Quetta market,Pakistan

Analysis of producers' and intermediaries' livestock price expectations was used to describe the market in Quetta, the largest livestock market in the highlands of Balochistan Province, Pakistan, and to identify factors that determine price expectations of small ruminants. A total of 4800 expected prices for sheep and goats were collected from producers and market intermediaries at monthly intervals between January 1991 and December 1992. In addition to the expected price of the animal, liveweight, species, sex, breed, body condition (fatness), calendar day and month were recorded, and whether data were collected on a meat or meatless day. Monthly rainfall data were also collected. Models of goat and sheep price expectations were built to compare the similarity of the behaviour of producers and intermediaries. Results indicated that producers and intermediaries expected high prices from November to January and during religious holidays. They expected premiums and discounts related to animals' attributes. Liveweight and seasonality had the strongest effect on prices. Rainfall in the current and previous month was positively related to seller's expected prices suggesting that livestock are retained to take advantage of favourable grazing conditions. The models of price expectations showed that producers adjusted expected goat prices (P ≤ 0.10) for seasonality, liveweight, body condition, age, sex and breed, while they adjusted sheep prices for seasonality and liveweight only. High pay-offs could be expected if extension efforts focused on factors that determine sheep meat quality; however, the retail ceiling price of meat and the lack of grading are a disincentive to work in this direction. Seasonality of supply and demand is important in determining prices and this study provides baseline information for market scheduling; however, scheduling of sales of transhumant pastoralists may be difficult to achieve. Further investigation is justified to understand the gap in marketing knowledge between producers who sell in the villages and those who sell in Quetta.