Acquisition Efforts Research Articles

Towards Monitoring of Nutrient Pollution in Coastal Lake Using Remote Sensing and Regression Analysis

The last few decades have witnessed a tremendous increase in nutrient levels (phosphorus and nitrogen) in coastal water leading to excessive algal growth (Eutrophication). The presence of large amounts of algae turns the water’s color into green or red, in the case of algal blooms. Chlorophyll-a is often used as an indicator of algal biomass. Due to increased human activities surrounding Dubai creek, there have been eutrophication concerns given the levels of nutrients in that creek. This study aims to map chlorophyll-a in Dubai Creek from WorldView-2 imagery and explore the relationship between chlorophyll-a and other eutrophication indicators. A geometrically- and atmospherically-corrected WorldView-2 image and in-situ data have been utilized to map chlorophyll-a in the creek. A spectral model, developed from the WorldView-2 multispectral image to monitor Chlorophyll-a concentration, yielded 0.82 R2 with interpolated in-situ chlorophyll-a data. To address the time lag between the in-situ data and the image, Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images were used to demonstrate the accuracy of the WorldView-2 model. The images, acquired on 20 May and 23 July 2012, were processed to extract chlorophyll-a band ratios (Band 4/Band 3) following the standard approach. Based on the availability, the 20 May image acquisition date is the closest to the middle of Quarter 2 (Q2) of the in-situ data (15 May). The 23 July 2012 image acquisition date is the closest to the WorldView-2 image date (24 July). Another model developed to highlight the relationship between spectral chlorophyll-a levels, and total nitrogen and orthophosphate levels, yielded 0.97 R2, which indicates high agreement. Furthermore, the generated models were found to be useful in mapping chlorophyll-a, total nitrogen, and orthophosphate, without the need for costly in-situ data acquisition efforts.

Antecedents of Knowledge Acquisition in Micro, Small and Medium Enterprises

Knowledge acquisition has gained several research areas, such as human resources, marketing, finance, performance, and so forth. It has been acknowledged as an essential path for business success. While firms recognize the importance of knowledge acquisition to enhance business performance, previous literature indicates that SME’s are limited in knowledge acquisition efforts corroborated by the limited research in knowledge sources. For SMEs, knowledge acquisition can be identified as a vital variable as its absence may often hamper the leverage of attaining firm objectives. The frugality of research in discussing the antecedent factors in knowledge acquisition unequivocally, in the Micro, Small and Medium Scale Enterprises is the motivation for the present study. Based on previous studies the study develops a conceptual framework to suggest a relationship between knowledge acquisition and four antecedent factors (domestic knowledge, market knowledge, technological knowledge, and environmental knowledge). A Questionnaire is proposed to collect data and Smart PLS would be used to analyze the data. Conclusion/Recommendations: This study attempts to discuss some of the precursor variables that can affect knowledge acquisition.

Projective Techniques for Understanding Cyber-Market Mavenism in Social Network Sites

Purpose – The purpose of this study is to identify consumers called market mavens in cyberspace whose viewpoints influence the attitude and behavior of other consumers . Further , the research aim is to create a better understanding of antecedents and consequences such behavior . Design / methodology / approach – After making rapport , participants were given a blank sheet and were asked to depict a cyber- market maven together with the environment in which he / she lives and the things of which he / she thinks . After drawing , participants were interviewed to answer questions associating with the picture’s elements , and thematic analysis was used to interpreting data. Findings – Interpretation of data indicated that seven factors determining cyber mavenism as well as three factors affected by such behaviour. Practical implications- The study is useful to those e-businesses wishing to target a consumer who people perceive as a good source of marketplace information and who likes introducing new brands to others , and use them as powerful sources in the context of co ‐ producing products . In addition , cyber- mavens can help e-businesses amplify their new customer acquisition efforts by indicating which customer groups they should target with referral reward programs . Originality / value – This study represents one of the first attempts to better understand how mavens behave in virtual world channels , and , by so doing , better inform our understanding of an important group of consumers , namely cyber- mavens . The paper could be of value to marketers and advertisers who target cyber- markets .

Limited attention and portfolio choice: The impact of attention allocation on mutual fund performance

AbstractThis study proposes that the performance of mutual fund managers is linked to how efficiently they allocate attention across assets in their investment set. Motivated by existing models of optimal portfolio choice and rational inattention, we posit that the efficiency of attention allocation increases when a manager chooses larger (smaller) active positions in assets that need more (less) information acquisition effort to resolve uncertainty about future payoffs. We show that the efficiency of attention allocation has a significantly positive impact on future fund performance. Efficient attention allocation has a lesser impact on performance as the total demands on a manager's limited attention increase.

Executive Compensation Packages and Customer Acquisition of Selected Deposit Money Banks in Lagos State Nigeria

Executive compensation is a major strategy being employed by deposit money banks to achieve steady growth in their customer acquisition efforts. The banks face series of challenges including inability to achieve consistent service excellence which had negatively impacted on new customer acquisition. The study examined the effect of executive compensation package on customer acquisition of selected deposit money banks in Lagos State, Nigeria. The study employed cross sectional survey research design where four hundred and twenty-nine copies of the research instruments were administered to purposively selected respondents who were senior and executive staff of the selected banks. The result of multiple regression analysis revealed that base salary (B = 0.217, p = 0.000) and recognition (B = 0.123, p = 0.012) have positive and significant effect on customer acquisition while supplementary benefits (B = 0.017, p = 0.568) and executive bonus (B = 0.044, p = 0.175) have positive, but insignificant effect on customer acquisition. The study concluded that executive compensation has positive effect on customer of selected deposit money banks in Lagos State, Nigeria. It was recommended that attractive compensation management should be instituted to ensure that executive staff are adequately remunerated to facilitate their performance with less distractions.

Reconstructing Six Decades of Surface Temperatures at a Shallow Lake

Lake surface water temperature (LSWT) plays a fundamental role in the lake energy budget. However, direct observations of LSWT require considerable effort for acquisition and hence are rare relative to a large number of lakes. In lakes where LSWT has not been covered sufficiently by in situ measurements, remote sensing and lake modeling can be used to produce a fine spatio-temporal record of LSWTs. In our study, the Moderate-Resolution Imaging Spectroradiometer (MODIS) LSWT was used to compare with in situ data at the overpass times over the six sites in Lake Chaohu, a large shallow lake in China. MODIS-derived LSWT reflected the variation of lake surface temperature well, with a correlation coefficient of 0.96 and a cool bias of 1.25 °C. The bias was modified by an “Upper Envelop” smoothing method and then employed to evaluate the general lake model (GLM) performance, a one-dimensional hydrodynamic model. The GLM simulations showed good performance compared with MODIS LSWT data at an interannual time scale. A 57-year record of simulated LSWT was hindcast by the well-calibrated GLM for Lake Chaohu. The results showed that LSWT decreased by 0.08 °C/year from 1960 to 1981 and then increased by 0.05 °C/year. These trends were most likely caused by a cooling effect of decreased surface incident solar radiation and a warming effect of reduced wind speed. Our study promoted the use of MODIS-derived LSWT as an alternative data source, and then combined with a numerical model for inland water surface temperature, and also further provided an understanding of climate warming effect on such a shallow eutrophic lake. Key points: (1) Moderate-Resolution Imaging Spectroradiometer (MODIS) lake water surface temperature (LSWT) was validated with real-time in situ data collected at Lake Chaohu with high accuracy; (2) MODIS LSWT was modified by the bias correction and employed to evaluate a one-dimensional lake model at interannual and intraannual scale; The LSWT hindcast by a well-calibrated model at Lake Chaohu decreased by 0.08 °C/year from 1960 to 1981 and increased by 0.05 °C/year from 1982 to 2016.

“Speaking of Purchases”: How Conversational Potential Determines Consumers' Willingness to Exert Effort for Experiential Versus Material Purchases

Consumers spend much of their incomes on two types of purchases: experiences and material objects. Recent research has successfully used this purchase type categorization to predict various types of social and psychological consumer outcomes. The present investigation extends this research to a novel domain of primary relevance to firms—that of consumer effort. Specifically, this work advances and tests the prediction that consumers are more willing to exert effort to acquire experiential versus material purchases. Further, drawing on literature on online and offline consumer interactions, it proposes that the greater conversational potential of experiences (vs. objects) explains this effect. Five studies employing mediation, moderation, and actual-choice approaches, applying different methodologies to purchases (past, future, and framed purchases) and testing different types of acquisition effort (e.g., to save money, to wait in a line to make the purchase) offer converging evidence in support of the predicted model. Theoretical and practical implications are discussed.

AN ANALYSIS OF THE USE OF TECHNOLOGY MANAGEMENT ACTIVITIES FOR TECHNOLOGY OPTIMISATION: A CASE IN THE BANKING INDUSTRY

Technology in the banking industry plays a key role in driving strategic business decisions. Technology acquisitions often do not result in optimal technology utilisation as measured by the number of innovations being logged, failure incidents in operations, and customer feedback ratings. The study investigates how technology management activities are carried out, with the emphasis on the acquisition and learning activities. A research model containing the elements of (i) technology acquisition effort, (ii) learning effort, (iii) innovative capacity, (iv) technology management tools limiting factors, and (v) technology optimisation was used to determine the inter-relationships between the elements. The research followed a mixed methods approach in which a quantitative study in the form of a survey, followed by qualitative interviews, was used. The research results confirmed the importance of the technology management activities and the need for coupling such activities. The study also identified shortcomings in terms of feedback loops in the technology management lifecycles.

Detection of interferences in an additive manufacturing process: an experimental study integrating methods of feature selection and machine learning

Additive manufacturing becomes a more and more important technology for production, mainly driven by the ability to realise extremely complex structures using multiple materials but without assembly or excessive waste. Nevertheless, like any high-precision technology additive manufacturing responds to interferences during the manufacturing process. These interferences – like vibrations – might lead to deviations in product quality, becoming manifest for instance in a reduced lifetime of a product or application issues. This study targets the issue of detecting such interferences during a manufacturing process in an exemplary experimental setup. Collection of data using current sensor technology directly on a 3D-printer enables a quantitative detection of interferences. The evaluation provides insights into the effectiveness of the realised application-oriented setup, the effort required for equipping a manufacturing system with sensors, and the effort for acquisition and processing the data. These insights are of practical utility for organisations dealing with additive manufacturing: the chosen approach for detecting interferences shows promising results, reaching interference detection rates of up to 100% depending on the applied data processing configuration.

Making seismic monitoring work in a complex desert environment — 4D processing

Seismic monitoring of an onshore carbonate reservoir in a desert environment has been achieved for the first time. Optimizing data repeatability was key to detecting the weak 4D (time-lapse) signal resulting from a fluid-injection program, which was achieved through a combination of specialized survey design, careful acquisition, and dedicated 4D processing. The hybrid acquisition system utilized buried geophones, which significantly reduced 4D noise caused by variability in the near-surface environment. Despite the extensive acquisition efforts, time-lapse processing is an essential component of achieving highly repeatable data. A fit-for-purpose workflow was developed to reduce the remaining 4D noise using a combination of parallel and simultaneous processing. Processing steps leading to the largest improvement in reflection signal-to-noise ratio, such as noise attenuation, amplitude balancing, and supergrouping, produced the largest reduction in 4D noise. Outstanding final migrated data repeatability has been achieved, comparable to levels reported for the more favorable permanent marine systems. However, the need to use surface sources results in a seasonal imprint on data repeatability, which hinders the interpretation of surveys acquired during different seasons. In the absence of a fully buried acquisition system, advanced processing techniques such as surface-consistent matching filters may be required to resolve these variations.

Engineering Value: The Returns to Technological Talent and Investments in Artificial Intelligence

Employees with technological skills are highly complementary to the intangible knowledge assets that firms accumulate. This paper describes how technical talent is a source of rents for corporate employers, particularly for the case of Google’s surprising open source launch of TensorFlow, a deep learning software package. First, I present a simple model of how employers intangible assets expose them to the returns to their employees’ skill acquisition efforts. Then, using over 180 million position records and over 52 million skill records from LinkedIn, I build a panel of firm-level skills to measure the market value of exposure to newly available deep learning talent. AI skills are strongly correlated with market value, though variation in AI skills from 2014-2017 does not explain contemporaneous revenue productivity within firms. AI-intensive companies rapidly gained market value following the launch of TensorFlow, while companies with opportunities to automate relatively larger quantities of labor with machine learning did not. Using a difference-in-differences approach, I show that the TensorFlow launch is associated with an approximate market value increase of $11 million per 1 percent increase in AI skills for AI-using firms. AI superstar firms in the top quintile also appear to benefit more over the sample period than less intensive adopters. These results suggest that the primary mechanism responsible for the market valuation increases of AI adopters at the time of the AI skill shock from TensorFlow is a revaluation of existing firm-specific technology-exposed assets.

Flowers, leaves or both? How to obtain suitable images for automated plant identification

BackgroundDeep learning algorithms for automated plant identification need large quantities of precisely labelled images in order to produce reliable classification results. Here, we explore what kind of perspectives and their combinations contain more characteristic information and therefore allow for higher identification accuracy.ResultsWe developed an image-capturing scheme to create observations of flowering plants. Each observation comprises five in-situ images of the same individual from predefined perspectives (entire plant, flower frontal- and lateral view, leaf top- and back side view). We collected a completely balanced dataset comprising 100 observations for each of 101 species with an emphasis on groups of conspecific and visually similar species including twelve Poaceae species. We used this dataset to train convolutional neural networks and determine the prediction accuracy for each single perspective and their combinations via score level fusion. Top-1 accuracies ranged between 77% (entire plant) and 97% (fusion of all perspectives) when averaged across species. Flower frontal view achieved the highest accuracy (88%). Fusing flower frontal, flower lateral and leaf top views yields the most reasonable compromise with respect to acquisition effort and accuracy (96%). The perspective achieving the highest accuracy was species dependent.ConclusionsWe argue that image databases of herbaceous plants would benefit from multi organ observations, comprising at least the front and lateral perspective of flowers and the leaf top view.

Robust optimal inventory and acquisition effort decisions in a hybrid manufacturing/remanufacturing system

ABSTRACTThis paper considers a stochastic multi-period inventory and acquisition effort decisions problem in a hybrid manufacturing/remanufacturing system. Different from past papers, two factors are introduced into the dynamic decision problem. One is the dependency between sales and returns, the other is the dual impacts of acquisition effort on the return of used products and the demand. Few past papers consider them, but they are important and unavoidable for many practical cases. These factors make the problem a high-dimensional decision-making problem, which is difficult to analyze and solve the optimal policy by stochastic dynamic programming, so we employ the robust optimization method. Based on the duality theory, an equivalent robust optimization model is given, which is a convex programming problem. By numerical analyses, we analyze the effects of system parameters on the related decisions and profits, which can provide insights for producers to manage their hybrid manufacturing/remanufacturing systems.

Construction sectors efficiency analysis on seven European countries

PurposeThe purpose of this paper is to measure and compare the technical efficiency of construction companies in seven European countries: Austria, Germany, Hungary, Italy, Poland, Portugal and Spain, during the 2008–2015 period. The analysis involves nine sectors grouped into three divisions: construction of buildings (F41), civil engineering (F42) and specialized construction activities (F43), by NACE classification.Design/methodology/approachMultidirectional efficiency analysis was adopted to investigate the levels of efficiencies, the differences in those levels and the possible causes of such differences by further defining two new indices.FindingsIt showed that F43 is the most efficient division during the study period, followed by F42 and F41. The sectors/countries with less efficiency are: construction of roads and railways/Poland, construction of other civil engineering projects/Hungary, demolition and site preparation/Poland, other specialized construction activities/Portugal. Globally, the development of building projects sector uses resources in the most inefficient way and there was a drop in the efficiency in 2011 and 2013, showing a delay in the crisis impact. After 2010, civil engineering projects required a substantial effort to access resources. Other features regarding (in)efficiency were further identified.Originality/valueThe analysis was conducted with one of the most effective techniques in frontier analysis. The first introduced index allows for comparing efficient/inefficient subgroups, and the other index measures the resource acquisition effort, allowing a better comparison along years. The study provides a good understanding of the performance of the construction industry and indirectly exposes the strategies to overcome the crisis, through the identification of the inputs/outputs which are well/badly used.

The unforeseen business and medical consequences of EHR data collection for a real-world data multiple myeloma registry.

e19528 Background: Record retrieval on behalf of a consenting patient within the context of real-world data is not well understood. As the need for real-world data continues to expand, methods for the efficient transfer of information across consenting parties will be critical to enable research collaborations. This need was highlighted through a partnership between COTA and the Multiple Myeloma Research Foundation (MMRF). As one component of the pilot study, COTA managed the record retrieval of consenting patients before going on to abstract the data for use in a registry. Methods: The pilot study identified 23 patients that consented to the release of medical records at 54 institutions across 20 states. COTA partnered with a retrieval vendor and employed its own outreach efforts for acquisition. Outreach and retrieval techniques were similar across COTA and the vendor, including targeted calls, delivery of IRB-approved consent materials, and on-site requests. The 30-day release parameter for a covered entity under 45 CFR 164.524(b)(2) of HIPAA’s Privacy Rule was used to evaluate the observed return rates. Results: A total of 56 medical records were requested, and 48 records were retrieved. The mean (±SD) retrieval time across all sites was 33 (±58) days. We found that 54% of records were released in < = 30 days, and 32% of records > 30 days. 14% of requested records were never released, despite a median of 19 outreach attempts (range 10 to 43). Cited issues for delay or non-release consisted of 22 institutions questioning the validity of the certified electronic patient signature, 6 requiring a physical signature, and 5 requiring their own authorization forms. In no cases did the records contain structured metadata, such as LOINC, MedDRA, and RxNorm. Conclusions: This pilot showed an unpredictable variance associated with the release of records in the context of real-world data. This variance contributed to barriers and delays in broader research efforts. The lack of accompanying metadata with released records resulted in additional required data processing. Future studies should be conducted to establish best practices in the release and retrieval of medical records used to support real-world data research.

Coupling and Decoupling of Soil Carbon and Nutrient Cycles Across an Aridity Gradient in the Drylands of Northern China: Evidence From Ecoenzymatic Stoichiometry

AbstractDrylands are characterized by stressful conditions with the limitation of both carbon (C) and nutrients, particularly nitrogen (N) and phosphorus (P). Biological C, N, and P releases from soil organic matter by enzymes are essential components for biogeochemical cycles and are sensitive to the climate in drylands. However, how the ecoenzymatic C:N:P stoichiometry responds to environmental factors (i.e., climatic and edaphic factors) over broad geographical scales remains largely unclear. We examined the patterns of ecoenzymatic C:N:P ratios across a 3,700‐km aridity gradient (0.43 < aridity < 0.97) in northern China. In wetter sites (aridity < 0.70), the relative C:N:P acquisition ratios via enzymes remained relatively constant with increasing aridity. In contrast, in drier sites (aridity > 0.70), the enzymatic C:nutrient (N and P) ratios declined as the aridity increased, while the enzymatic P:N ratios were mostly lower than those in the wetter sites. In drier sites with low C availability, the increasing carbon use efficiency and the increasing proportion of C converted to biomass (than the proportion of respiration) contributed to the declines of the enzymatic C:nutrient ratios as the aridity increased. The overall lower enzymatic P:N ratios were related to the higher soil P availability compared with N availability (higher organic P and lower soil NH4+:available P ratios) in drier sites. Overall, our findings indicate that intrinsic linkages of biological C, N, and P acquisitions and cycles were broken at the aridity threshold of 0.70, with higher acquisition efforts for N and P (particularly for N) with increasing aridity in drier sites with aridity > 0.70.

Task Acquisition and Motor Learning Require Conscious Efforts by The Patients

Task Acquisition and Motor Learning Require Conscious Efforts by The Patients

Salt structures from inversion of residual gravity anomalies: application in Santos Basin, Brazil

The Santos Basin, with an area of about 350.000 km2 , is the largest salt basin of the South Atlantic, and due to its high economic hydrocarbon potential, it is a recurrent theme in scientific studies. The salt structures over the region present great importance for hydrocarbon accumulation and the geological/geophysical studies are performed from seismic reflection data, which requires time and efforts for acquisition and data processing. We identify salt structures using a new workflow based on inversion of residual gravity anomalies, where we use the Moho and basement depths obtained from gravity inversion, followed by the calculation of the gravity residual anomaly, assumed to be representative of the salt structures. This workflow is tested for a geological profile in the Santos Basin, and the results are evaluated along a 2D seismic section tied to well markers. The geometry of the stratified salt obtained from gravity inversion correlates with the seismic interpretation, with the advantage of estimating the entire salt package, including halite and stratified salt. With only seismic data, sometimes the stratified salt can be misinterpreted as sediments. The procedure can be applied to identify salt in sedimentary basins where seismic data is unavailable or of low quality.

Information, Participation, and Passive Investing

I investigate the impact of fundamental information acquisition costs on price informativeness and passive investing. Within a REE model of multiple risky assets and a redundant market index, I define passive investing as the optimal decision to: 1) free-ride on the information acquisition efforts of active traders in the index asset, and 2) forgo all stock picking strategies. Falling information costs have the dual effect of lowering the cost of market timing, decreasing passive share, and lowering the cost of stock picking, increasing passive share. If the stock picking effect dominates the market timing effect, passive share increases in tandem with greater price informativeness. I exploit SEC's eXtensible Business Reporting Language mandate as a negative shock to information costs to provide suggestive evidence that falling information costs may be contributing to the rise in passive investing.

How to measure marketing success and find your cost per new student acquisition

Marketing dollars need to be justified, and tying spending to both direct and indirect results can help clarify marketing efforts and aid in decision-making. Far too often, educational institutions build marketing campaigns around creative concepts and overlook the necessary element of measurement. Developing methods for evaluating brand and acquisition efforts are challenging. This paper looks at ways to develop metrics that can assist in measuring marketing success through concepts like brand recall and cost per new student acquisition. College executives have opportunities available to build reporting that clearly communicates value in marketing campaigns. After reviewing measurement methodologies, the paper will evaluate a real-world case study to explore ideas for building a marketing plan and generating reports that demonstrate success.