200,571 research outputs found
Consumer Information Search and Decision-Making on M-Commerce
No full textThis study compares consumer decision-making experiences across two channels (m-commerce and e-commerce), and investigates the moderating role of product type in each channel. Cognitive cost, the technology acceptance model, unified theory of acceptance and use of technology, and social cognition theory are used to formulate propositions. E-mail messages sent by the participants after undertaking a decision-making task on a channel are analyzed using Critical Incident Technique (CIT). Study findings suggest that product type moderates consumer decision-making on both channels. Findings also suggest that decision-making in m-commerce is perceived as stressful. Findings also highlight the differences between the two channels. The chapter concludes with managerial and theoretical implications and directions for future research
Consumer Decision-Making: Critical Factors for M-Commerce
No full textThis study compares consumer decision-making experiences across three channels (i.e., m-commerce, e-commerce, in-store), identifies factors affecting consumer decision-making that are unique to a specific channel as well as those that are common across the three channels, and suggests a model for intention to use m-commerce. Cognitive cost, expectation-confirmation theory, theory of reasoned action and technology acceptance model are used to formulate propositions. E-mail messages sent by the participants after undertaking a decision-making task on a channel are analyzed using Critical Incident Technique (CIT). Study findings suggest that decision-making in m-commerce is perceived as stressful and is not necessarily a positive one. Findings further suggest that participants in m-commerce hold their prior experiences in e-commerce as points-of-reference to which they compare subsequent decision-making experiences. Findings also reveal factors that affect consumer decision-making experience negatively on m-commerce. The article concludes with managerial and theoretical implications and directions for future research
Critical factors of consumer decision-making on m-commerce: a qualitative study in the United States
No full textThis study compares consumer decision-making experiences across three channels (m-commerce, e-commerce, in-store), identifies factors affecting consumer decision-making that are unique to a specific channel as well as those that are common across the three channels, and suggests a model for intention to use m-commerce. Cognitive cost, expectation-confirmation theory, theory of reasoned action and the technology acceptance model are used to formulate propositions. E-mail messages sent by the participants after undertaking a decision-making task on a channel are analyzed using Critical Incident Technique (CIT). Study findings suggest that decision-making in m-commerce is perceived as stressful and is not necessarily a positive one. Findings further suggest that participants in m-commerce hold their prior experiences in e-commerce as points-of-reference to which they compare subsequent decision-making experiences. Findings also reveal factors that affect consumer decision-making experience negatively on m-commerce. The article concludes with managerial and theoretical implications and directions for future research
Consumer decision-making across modern and traditional channels: E-commerce, m-commerce, in-store
No full textThis study investigates the effect of media richness on consumer decision-making and channel choice, and grounds the investigation in media richness theory, task-media fit hypotheses and cognitive cost (behavioral decision theory). Findings from three experiments provide evidence that consumers prefer channels with medium (e.g., e-commerce) and high (e.g., in-store) media richness for carrying out complex decision-making tasks. Findings reveal that consumers are likely to undertake simple decision-making tasks on channels that incorporate low (e.g., m-commerce) levels of media richness. Findings also demonstrate that product type moderates the effect of media richness on perceived channel-task fit, post-purchase evaluation, and channel choice. These insights should prove helpful to managers in managing content across different channels
Haematopota marginata Ricardo 1911
No full text8. Haematopota marginata Ricardo, 1911 1911. Haematopota marginata Ricardo, Rec. Indian Mus., 4: 347. Type locality: Pusa, Bihar. Material examined: 1♀, collected from cow, 23°17 ʹ 25.29 ʺ N, 87°15 ʹ 2.58 ʺ E, 92.9 m, Station 1, Bankura, 20.ii.2014, Coll. A. Maity; 1♀, collected from cow, 23°15'18.73"N, 87°25'49.44"E, 83.5 m, Station 10, Bankura, 20.ii.2014, Coll. A. Maity. Distribution: India (West Bengal: Birbhum; Assam, Bihar, Meghalaya). Elsewhere: Bangladesh. Remarks: This species is commonly found in hilly region of North Bengal.Published as part of Maity, Aniruddha, Naskar, Atanu, Homechaudhuri, Sumit & Banerjee, Dhriti, 2020, Taxonomic Accounts With Notes On Spatial Diversity And Relative Abundance Pattern Of Horseflies (Diptera: Tabanidae) From Sonamukhi Protected Forest Area Of West Bengal, India, pp. 200-225 in Munis Entomology & Zoology 15 (1) on page 213, DOI: 10.5281/zenodo.376195
Tabanus (Tabanus) striatus Fabricius, Mantissa Insect 1787
No full text5. Tabanus (Tabanus) striatus Fabricius, 1787 1787. Tabanus striatus. Fabricius, Mantissa insect, 2: 356. Type locality: China. Material examined: 7♀♀, collected from cow, 23°16'23.26"N, 87°22'32.06"E, 83.2 m, Station 7, Bankura, 27.ix.2013, Coll. R.S. Mridha; 1♀, collected from cow, 6♀♀, collected from buffalo, 23°17'24.55"N, 87°24'52.28"E, 76.4 m, Station 8, Bankura, 29.ix.2013, Coll. R.S. Mridha; 2♀♀, collected from cow, 23°17'24.55"N, 87°24'52.28"E, 76.4 m, Station 8, Bankura, 29.ix.2013, Coll. S.K. Sinha; 10♀♀, collected from cow, 23°16'23.26"N, 87°22'32.06"E, 83.2 m, Station 7, Bankura, 27.vii.2014, Coll. A. Maity; 7♀♀, collected from buffalo, 23°16'23.26"N, 87°22'32.06"E, 83.2 m, Station 7, Bankura, 26.vii.2014, Coll. A. Maity; 1♀, collected from cow, 23°13'31.79"N, 87°23'50.42"E, 84.9 m, Station 9, Bankura, 20.iv.2014, Coll. A. Maity; 1♀, collected from cow, 23°15'18.73"N, 87°25'49.44"E, 83.5 m, Station 10, Bankura, 20.iv.2014, Coll. A. Maity. Distribution: India (West Bengal: Alipurduar, Bankura, Birbhum, Bardhaman, Darjeeling, East Midnapore, Hooghly, Howrah, Jalpaiguri, Kolkata, Maldah, Murshidabad, N 24 Paragana, Nadiya, Puruliya, S 24 Paragana, S Dinazpur, West Midnapore; Arunachal Pradesh, Assam, Bihar, Delhi, Gujrat, Himachal Pradesh, Jammu & Kashmir, Karnataka, Kerala, Madhya Pradesh, Maharastra, Manipur, Meghalaya, Nagaland, Orissa, Punjab, Sikkim, Tamil Nadu, Tripura, Uttarakhand, Uttar Pradesh). Elsewhere: Bangladesh, Bhutan, Combodia, China, Laos, Myanmar, Nepal, Pakistan, Sri Lanka, Thailand and Vietnam. Remarks: There was taxonomic misinterpretation through ages and hence the distributional records associated with the species were in a mess everywhere before Burton (1978) who took pains to sort out the perplexed identity of the species from its allies. Later, Burger and Thompson (1981) aptly illustrated, keyed and discussed these species with a view to making away with the recurrent confusion. This is a very common and widespread species in India, and is often found to enter the house, being attracted by light in hot summer night.Published as part of Maity, Aniruddha, Naskar, Atanu, Homechaudhuri, Sumit & Banerjee, Dhriti, 2020, Taxonomic Accounts With Notes On Spatial Diversity And Relative Abundance Pattern Of Horseflies (Diptera: Tabanidae) From Sonamukhi Protected Forest Area Of West Bengal, India, pp. 200-225 in Munis Entomology & Zoology 15 (1) on page 212, DOI: 10.5281/zenodo.376195
Predicting the compressive strength of unreinforced brick masonry using machine learning techniques validated on a case study of a museum through nondestructive testing
No full textHistorical buildings, such as museums, are an important class of buildings because ancient historical artefacts are collected and preserved in them. These buildings must be maintained to prolong their service life and monitored continuously for possible signs of building damages. Determining the compressive strength is essential for predicting the remaining service life of museums because monumental museum buildings usually comprise load-bearing masonry walls. This study analysed the applicability of three machine learning techniques as alternative methods for predicting the compressive strength of masonry constructions. A database was established by performing experimental testing on 44 masonry specimens. In the nondestructive techniques used, the ultrasonic pulse velocity and the rebound number were inputs and the compressive strength of masonry unit (fmu) was the desired output. The remaining compressive strength of a museum was determined using commonly available nondestructive testing apparatus. The model predictions obtained through nondestructive measurements were compared with the experimental results obtained through the destructive testing of masonry units in the laboratory. The proposed approach was compared with traditional empirical models and commonly used machine learning techniques. The analyses revealed that machine learning techniques are robust, can successfully be used for the prediction of the remaining compressive strength of historical constructions, and thus can provide decision support for inspection professionals
Tabanus (Tabanus) rubidus Wiedemann 1821
No full text4. Tabanus (Tabanus) rubidus Wiedemann, 1821 1821. Tabanus rubidus Wiedemann, Dipt. Exot., 1: 69. Type locality: Bengalia. Material examined: 2♀♀, collected from cow, 23°17'24.55"N, 87°24'52.28"E, 76.4 m, Station 8, Bankura, 20.iv.2014, Coll. A. Maity; 5♀♀, collected from cow, 23°16'23.26"N, 87°22'32.06"E, 83.2 m, Station 7, Bankura, 27.ix.2013, Coll. A. Naskar. Distribution: India (West Bengal: Bankura, Birbhum, Hooghly, Maldah; Arunachal Pradesh, Meghalaya, Orissa, Sikkim). Elsewhere: Pakistan, Philippines, China, Indonesia. Remarks: This species is very common across different study area of West Bengal. This species shows wide distribution pattern across different districts of the state.Published as part of Maity, Aniruddha, Naskar, Atanu, Homechaudhuri, Sumit & Banerjee, Dhriti, 2020, Taxonomic Accounts With Notes On Spatial Diversity And Relative Abundance Pattern Of Horseflies (Diptera: Tabanidae) From Sonamukhi Protected Forest Area Of West Bengal, India, pp. 200-225 in Munis Entomology & Zoology 15 (1) on pages 211-212, DOI: 10.5281/zenodo.376195
Dr. Duane M. Jackson, Morehouse College, July 2011
No full textThis video is a conversation with Dr. Duane M. Jackson. Dr. Jackson talks about his paper, "Recall and the Serial Position Effect: The Role of Primacy and Recency on Accounting Students' Performance." Jackie Daniel, AUC Woodruff Library, is the interviewer
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