Elevate your influence: EDBA research topics for industry architects

Description of the video:

WEBVTT 1 00:00:00.000 --> 00:00:01.280 2 00:00:01.280 --> 00:00:04.360 My research interest lies in the intersection 3 00:00:04.360 --> 00:00:06.960 of international business and sustainability. 4 00:00:06.960 --> 00:00:10.960 So basically, I study how firm tackle the complexity 5 00:00:10.960 --> 00:00:14.880 of operating globally while simultaneously pursuing 6 00:00:14.880 --> 00:00:19.400 making a positive impact on social and environmental space. 7 00:00:19.400 --> 00:00:23.240 So this challenge really comes from the heterogeneity 8 00:00:23.240 --> 00:00:26.600 of institutional environments across different countries 9 00:00:26.600 --> 00:00:31.620 and also the conflicting stakeholder demands worldwide. 10 00:00:31.620 --> 00:00:36.000 For instance, global investors looking for shareholder returns 11 00:00:36.000 --> 00:00:39.920 and ESG compliance, while local communities looking 12 00:00:39.920 --> 00:00:43.040 for social and environmental justice, 13 00:00:43.040 --> 00:00:47.240 and governments looking for the national industry security, 14 00:00:47.240 --> 00:00:50.920 so that firms really need to tackle this complexity. 15 00:00:50.920 --> 00:00:54.120 And meanwhile, this provides opportunity for them 16 00:00:54.120 --> 00:00:57.080 to develop competitive advantage by developing 17 00:00:57.080 --> 00:00:59.340 innovative sustainability strategies. 18 00:00:59.340 --> 00:01:03.640 So it's really fun that essentially every strategy 19 00:01:03.640 --> 00:01:07.880 or management issues has an international business lens. 20 00:01:07.880 --> 00:01:11.240 So this is why it's really exciting and great opportunity 21 00:01:11.240 --> 00:01:14.320 for our EDBA students because there 22 00:01:14.320 --> 00:01:16.460 are so many applied research questions. 23 00:01:16.460 --> 00:01:20.300 For instance, if you work for multinational companies, 24 00:01:20.300 --> 00:01:25.370 you might suddenly wake up to a raised tariff or a supply chain 25 00:01:25.370 --> 00:01:26.530 disruption. 26 00:01:26.530 --> 00:01:32.410 And/or you will have to face the challenge between globalization 27 00:01:32.410 --> 00:01:34.550 and techno-nationalism. 28 00:01:34.550 --> 00:01:38.190 So on the one hand, firms want to expand everywhere. 29 00:01:38.190 --> 00:01:41.990 However, we also face rising nationalism sentiment, 30 00:01:41.990 --> 00:01:45.170 particularly dual political nationalism. 31 00:01:45.170 --> 00:01:49.790 So how do firms and managers navigate this challenge, 32 00:01:49.790 --> 00:01:54.350 the dual forces, but meanwhile make global competitiveness? 33 00:01:54.350 --> 00:01:56.850 So I think this is a real puzzle and really 34 00:01:56.850 --> 00:02:00.090 exciting opportunities for our EDBA students. 35 00:02:00.090 --> 00:02:02.530 And if you like sustainability, here 36 00:02:02.530 --> 00:02:04.930 comes another layer of complexity. 37 00:02:04.930 --> 00:02:08.449 For instance, how do global coffee chains 38 00:02:08.449 --> 00:02:12.810 respond to climate shock that hit farmers 39 00:02:12.810 --> 00:02:15.370 in Colombia or Ethiopia? 40 00:02:15.370 --> 00:02:22.290 How do fashion retailers respond to the ever-evolving customer 41 00:02:22.290 --> 00:02:24.610 taste, but meanwhile, we need to manage 42 00:02:24.610 --> 00:02:27.310 expectations to reduce waste. 43 00:02:27.310 --> 00:02:30.810 So all those are true puzzles there that our managers 44 00:02:30.810 --> 00:02:32.510 face every day. 45 00:02:32.510 --> 00:02:36.730 And then that makes really exciting research opportunities 46 00:02:36.730 --> 00:02:39.740 for our EDBA students. 47 00:02:39.740 --> 00:02:44.000

Description of the video:

WEBVTT 1 00:00:00.000 --> 00:00:00.880 2 00:00:00.880 --> 00:00:03.520 My research is mainly interested in how 3 00:00:03.520 --> 00:00:05.220 to design effective teams. 4 00:00:05.220 --> 00:00:07.360 So I've done research on the role of autonomy 5 00:00:07.360 --> 00:00:09.140 in predicting team effectiveness. 6 00:00:09.140 --> 00:00:11.000 I've done research on how to compose 7 00:00:11.000 --> 00:00:13.080 a team of individual members, with varying 8 00:00:13.080 --> 00:00:15.480 levels of personality, to make those teams more 9 00:00:15.480 --> 00:00:19.560 likely to help one another and also perform better in the end. 10 00:00:19.560 --> 00:00:21.240 And another stream of research that I 11 00:00:21.240 --> 00:00:25.900 have is concerned with workplace health and employee stress. 12 00:00:25.900 --> 00:00:28.400 So I'm interested in how it is at different work design 13 00:00:28.400 --> 00:00:32.680 factors, whether it's the amount of job demands in someone's 14 00:00:32.680 --> 00:00:36.040 role, the level of social support, job control, 15 00:00:36.040 --> 00:00:38.600 and even some of the characteristics of employees 16 00:00:38.600 --> 00:00:42.160 that might impact the extent to which those stressors at work 17 00:00:42.160 --> 00:00:44.960 impact their health outside of work. 18 00:00:44.960 --> 00:00:46.780 So when I think about EDBA research, 19 00:00:46.780 --> 00:00:50.480 I think of research that has direct practical application. 20 00:00:50.480 --> 00:00:53.960 So think research that you can do in your current organization, 21 00:00:53.960 --> 00:00:56.400 or that you can do on another organization in a given 22 00:00:56.400 --> 00:00:59.400 industry, or research that really addresses questions 23 00:00:59.400 --> 00:01:01.642 that you're struggling with in your day-to-day work. 24 00:01:01.642 --> 00:01:03.600 So a couple of ideas that relate to my research 25 00:01:03.600 --> 00:01:05.805 streams that could potentially apply here. 26 00:01:05.805 --> 00:01:08.180 If a student were interested in studying employee health, 27 00:01:08.180 --> 00:01:10.360 for example, we could try an intervention, 28 00:01:10.360 --> 00:01:13.480 where part of the individuals in the organization 29 00:01:13.480 --> 00:01:15.700 might get more control over their work. 30 00:01:15.700 --> 00:01:17.760 Maybe we do a supervisor support intervention, 31 00:01:17.760 --> 00:01:20.060 where we train supervisors to be more supportive. 32 00:01:20.060 --> 00:01:21.880 And then we have another group of supervisors that doesn't 33 00:01:21.880 --> 00:01:23.380 receive training right away. 34 00:01:23.380 --> 00:01:25.800 And we compare the effectiveness of those teams 35 00:01:25.800 --> 00:01:27.800 and the well-being outcomes of those individuals 36 00:01:27.800 --> 00:01:29.920 that are under those supervisors. 37 00:01:29.920 --> 00:01:32.480 That could be one way of applying some of the stress 38 00:01:32.480 --> 00:01:34.760 research to an organizational context 39 00:01:34.760 --> 00:01:38.640 in a very focused and applied EDBA type of way. 40 00:01:38.640 --> 00:01:40.360 Something we could do on the team side 41 00:01:40.360 --> 00:01:43.020 is we might be interested in understanding, for example, 42 00:01:43.020 --> 00:01:46.120 how it is that different work from home policies impact team 43 00:01:46.120 --> 00:01:46.932 performance? 44 00:01:46.932 --> 00:01:49.640 If they work in an organization, where some people work from home 45 00:01:49.640 --> 00:01:52.520 and some people don't, we could use different methods 46 00:01:52.520 --> 00:01:54.460 to tease out those effects and see, OK, 47 00:01:54.460 --> 00:01:57.680 to what extent is working from home associated with higher team 48 00:01:57.680 --> 00:01:59.800 performance, or higher team cohesion, 49 00:01:59.800 --> 00:02:01.880 or other types of team outcomes that we're 50 00:02:01.880 --> 00:02:04.600 interested in the organizational sciences. 51 00:02:04.600 --> 00:02:06.480 So those are just two ideas of ways 52 00:02:06.480 --> 00:02:08.840 that EDBA students can leverage some of the research 53 00:02:08.840 --> 00:02:11.039 that I've done before in either teams 54 00:02:11.039 --> 00:02:12.620 or in the employee health domain. 55 00:02:12.620 --> 00:02:14.840 But there's many, many different questions 56 00:02:14.840 --> 00:02:17.000 that we could ask and explore together 57 00:02:17.000 --> 00:02:19.640 that will help us answer some very applied, interesting 58 00:02:19.640 --> 00:02:21.920 questions that are of relevance to organizations 59 00:02:21.920 --> 00:02:22.720 and policymakers. 60 00:02:22.720 --> 00:02:26.070 [WHIRRING] 61 00:02:26.070 --> 00:02:28.000

Description of the video:

WEBVTT 1 00:00:00.000 --> 00:00:01.360 2 00:00:01.360 --> 00:00:04.400 I'm really interested in researching leadership 3 00:00:04.400 --> 00:00:05.780 and individual differences. 4 00:00:05.780 --> 00:00:07.280 So individual differences are things 5 00:00:07.280 --> 00:00:10.120 like personality or intelligence or gender 6 00:00:10.120 --> 00:00:11.760 or those types of things. 7 00:00:11.760 --> 00:00:15.460 I've also been interested lately in generational differences. 8 00:00:15.460 --> 00:00:17.840 We're hearing a lot about, oh, the workers 9 00:00:17.840 --> 00:00:20.320 these days compared to the old days. 10 00:00:20.320 --> 00:00:23.520 So I'm interested in finding out how much of that is real 11 00:00:23.520 --> 00:00:25.780 and how much of it is stereotypes. 12 00:00:25.780 --> 00:00:29.600 One of the things that I'm excited about looking into more 13 00:00:29.600 --> 00:00:31.020 is remote work. 14 00:00:31.020 --> 00:00:33.800 Again, that's something that's been more and more popular 15 00:00:33.800 --> 00:00:34.420 these days. 16 00:00:34.420 --> 00:00:37.560 One of the challenges with that, though, is how do you still 17 00:00:37.560 --> 00:00:41.240 have that connection and keep people motivated when they're 18 00:00:41.240 --> 00:00:42.660 not around their team as much? 19 00:00:42.660 --> 00:00:45.280 What leader behaviors are going to make 20 00:00:45.280 --> 00:00:48.360 that transition more successful and the team more 21 00:00:48.360 --> 00:00:49.800 successful as a whole? 22 00:00:49.800 --> 00:00:52.800 So something that the EDBA students could work on 23 00:00:52.800 --> 00:00:56.120 are generational differences across the workplace. 24 00:00:56.120 --> 00:00:58.060 One question they could address, again, 25 00:00:58.060 --> 00:01:00.180 is looking at these generational differences. 26 00:01:00.180 --> 00:01:03.680 For example, are they real or are they 27 00:01:03.680 --> 00:01:06.400 self-fulfilling prophecies that people are seeing? 28 00:01:06.400 --> 00:01:09.420 And if they are real, what can we do about them? 29 00:01:09.420 --> 00:01:11.360 Are there specific leader behaviors 30 00:01:11.360 --> 00:01:15.520 that are going to influence whether or not people are 31 00:01:15.520 --> 00:01:17.540 motivated across generations? 32 00:01:17.540 --> 00:01:19.160 So that's one example. 33 00:01:19.160 --> 00:01:22.720 So another question an Executive DBA student might be asking 34 00:01:22.720 --> 00:01:25.985 is perhaps you self-promote a lot of people. 35 00:01:25.985 --> 00:01:27.360 So you have people that are going 36 00:01:27.360 --> 00:01:31.340 from individual contributors to now managers. 37 00:01:31.340 --> 00:01:32.820 A lot of organizations do that. 38 00:01:32.820 --> 00:01:35.120 And if you do that, you know that not everyone 39 00:01:35.120 --> 00:01:38.300 makes that transition as smoothly as everyone. 40 00:01:38.300 --> 00:01:40.980 So a question you might ask is, in your industry, 41 00:01:40.980 --> 00:01:43.420 are there certain personality characteristics, 42 00:01:43.420 --> 00:01:48.280 certain behaviors that help individual contributors become 43 00:01:48.280 --> 00:01:51.710 leaders of others more quickly? 44 00:01:51.710 --> 00:01:56.000

Description of the video:

WEBVTT 1 00:00:00.000 --> 00:00:01.440 2 00:00:01.440 --> 00:00:02.558 I'm a strategy professor. 3 00:00:02.558 --> 00:00:04.100 So ultimately, at the end of the day, 4 00:00:04.100 --> 00:00:05.475 my goal is to understand anything 5 00:00:05.475 --> 00:00:08.000 that would be a reason or an explanation for why 6 00:00:08.000 --> 00:00:10.560 one organization outperforms another. 7 00:00:10.560 --> 00:00:12.382 So specifically within that realm, 8 00:00:12.382 --> 00:00:13.840 I'm looking at firm governance, I'm 9 00:00:13.840 --> 00:00:17.040 looking at firm resources, especially human capital. 10 00:00:17.040 --> 00:00:18.520 In thinking about the opportunity 11 00:00:18.520 --> 00:00:20.760 to bring more individuals from practice 12 00:00:20.760 --> 00:00:23.720 into this specific program, I think 13 00:00:23.720 --> 00:00:26.280 there's several opportunities for the types of research 14 00:00:26.280 --> 00:00:27.553 we can conduct. 15 00:00:27.553 --> 00:00:29.720 One consideration is that a lot of strategy research 16 00:00:29.720 --> 00:00:31.120 is across organizations. 17 00:00:31.120 --> 00:00:32.720 And we're trying to compare why is it 18 00:00:32.720 --> 00:00:35.180 that one organization outperformed another? 19 00:00:35.180 --> 00:00:38.200 So in terms of framing and positioning potential research 20 00:00:38.200 --> 00:00:41.300 questions that are a bit more applied in nature, 21 00:00:41.300 --> 00:00:44.102 we can still anchor off the initial themes 22 00:00:44.102 --> 00:00:45.560 but then think about how this might 23 00:00:45.560 --> 00:00:47.880 be true in your own organization, where 24 00:00:47.880 --> 00:00:50.320 you might have some privileged data access. 25 00:00:50.320 --> 00:00:52.400 So as an example of some of the streams that I'm 26 00:00:52.400 --> 00:00:54.840 part of that students in this program 27 00:00:54.840 --> 00:00:57.000 might be able to conduct further research, 28 00:00:57.000 --> 00:00:59.560 first I'd start with the idea that a CEO can't 29 00:00:59.560 --> 00:01:01.820 take on every task themselves. 30 00:01:01.820 --> 00:01:03.800 And so they're constantly having to evaluate 31 00:01:03.800 --> 00:01:07.160 which tasks do I assign or leverage and delegate 32 00:01:07.160 --> 00:01:09.740 responsibility to other individuals. 33 00:01:09.740 --> 00:01:11.620 So in our work, we're specifically 34 00:01:11.620 --> 00:01:13.820 in the mergers and acquisitions context, 35 00:01:13.820 --> 00:01:17.060 saying, which M&A deals did the CEO personally 36 00:01:17.060 --> 00:01:19.220 retain responsibility for versus when 37 00:01:19.220 --> 00:01:21.940 did they lean on other members of their executive team 38 00:01:21.940 --> 00:01:22.940 more heavily. 39 00:01:22.940 --> 00:01:25.420 So a student in this program might consider, 40 00:01:25.420 --> 00:01:27.980 are there other tasks within your organization 41 00:01:27.980 --> 00:01:30.240 where there'd be varying levels of delegation? 42 00:01:30.240 --> 00:01:34.340 And can we build out a data set to explore that more deeply? 43 00:01:34.340 --> 00:01:37.080 A second interface would be on the governance dimensions. 44 00:01:37.080 --> 00:01:38.740 So obviously, in your organization, 45 00:01:38.740 --> 00:01:40.900 there's probably multiple different areas 46 00:01:40.900 --> 00:01:43.760 where you have committees that need to make decisions, 47 00:01:43.760 --> 00:01:46.340 or you have governance oversight boards 48 00:01:46.340 --> 00:01:50.220 that are choosing when to engage on certain key strategic 49 00:01:50.220 --> 00:01:51.460 decisions. 50 00:01:51.460 --> 00:01:55.060 So it's really important in the research 51 00:01:55.060 --> 00:01:58.380 that I do that we understand what checks and balances are 52 00:01:58.380 --> 00:02:03.460 in place that would overlay on top of the decisions 53 00:02:03.460 --> 00:02:05.360 that somebody is trying to execute. 54 00:02:05.360 --> 00:02:07.700 So to the extent that you can identify key decisions 55 00:02:07.700 --> 00:02:11.060 within your organization, and identify the governance 56 00:02:11.060 --> 00:02:13.740 mechanisms, then that would be a potential interest 57 00:02:13.740 --> 00:02:14.940 to governance scholars. 58 00:02:14.940 --> 00:02:18.290 [WHIRRING] 59 00:02:18.290 --> 00:02:20.000

Description of the video:

WEBVTT 1 00:00:00.000 --> 00:00:01.640 2 00:00:01.640 --> 00:00:04.780 So my broad research interest is entrepreneurship. 3 00:00:04.780 --> 00:00:06.240 But underneath that umbrella, I'm 4 00:00:06.240 --> 00:00:09.140 really interested in entrepreneurial strategy. 5 00:00:09.140 --> 00:00:12.260 So what makes newer ventures competitive, 6 00:00:12.260 --> 00:00:14.960 allowing them to compete and often outcompete 7 00:00:14.960 --> 00:00:16.239 larger ventures. 8 00:00:16.239 --> 00:00:17.640 And then in addition to that, I'm 9 00:00:17.640 --> 00:00:20.120 interested in how they get resources, 10 00:00:20.120 --> 00:00:23.320 what they do to be very resourceful in resource 11 00:00:23.320 --> 00:00:25.240 constrained environments, and what 12 00:00:25.240 --> 00:00:29.840 they do to convince others to give them resources as they 13 00:00:29.840 --> 00:00:32.119 grow, develop, and scale. 14 00:00:32.119 --> 00:00:35.620 So one of my most intriguing projects, at least to me, 15 00:00:35.620 --> 00:00:37.880 is about entrepreneurial hustle. 16 00:00:37.880 --> 00:00:42.240 We started off, myself and some of my PhD students, 17 00:00:42.240 --> 00:00:46.640 examining and carefully scrutinizing transcripts 18 00:00:46.640 --> 00:00:48.700 from how I built this podcast. 19 00:00:48.700 --> 00:00:51.640 So podcasting had emerged as a phenomenon. 20 00:00:51.640 --> 00:00:53.280 All these interesting entrepreneurs 21 00:00:53.280 --> 00:00:55.760 were being interviewed about what they had 22 00:00:55.760 --> 00:00:57.420 done to build their businesses. 23 00:00:57.420 --> 00:01:01.300 And we started analyzing what they said about what they did. 24 00:01:01.300 --> 00:01:04.440 And from that induced this concept 25 00:01:04.440 --> 00:01:06.640 of entrepreneurial hustle, which is 26 00:01:06.640 --> 00:01:11.360 acting with a sense of urgency and unorthodoxy 27 00:01:11.360 --> 00:01:13.920 to solve pressing problems. 28 00:01:13.920 --> 00:01:19.420 And we deduced this concept, defined it very strategically, 29 00:01:19.420 --> 00:01:23.880 then began to unpack how it's impacted venture development. 30 00:01:23.880 --> 00:01:27.680 And from that, translated it into another research paper, 31 00:01:27.680 --> 00:01:31.920 in which we came up with a very robust measure for how 32 00:01:31.920 --> 00:01:33.440 you might account for it. 33 00:01:33.440 --> 00:01:35.920 And connected that, or correlated 34 00:01:35.920 --> 00:01:37.960 that with venture success. 35 00:01:37.960 --> 00:01:42.000 So it was a project that started in podcasts, 36 00:01:42.000 --> 00:01:45.140 translated into an instrument to measure that, 37 00:01:45.140 --> 00:01:47.480 and then used in the field to test 38 00:01:47.480 --> 00:01:49.800 whether entrepreneurial hustle actually 39 00:01:49.800 --> 00:01:51.740 impacted venture success. 40 00:01:51.740 --> 00:01:55.090 [WHIRRING] 41 00:01:55.090 --> 00:01:57.000

Description of the video:

WEBVTT 1 00:00:00.000 --> 00:00:02.440 2 00:00:02.440 --> 00:00:04.080 My research interest for years has 3 00:00:04.080 --> 00:00:05.997 been in the area of corporate entrepreneurship 4 00:00:05.997 --> 00:00:07.080 and corporate innovation. 5 00:00:07.080 --> 00:00:09.560 Actually, I built my career based on that. 6 00:00:09.560 --> 00:00:11.720 It was the consulting that I did in major Fortune 7 00:00:11.720 --> 00:00:13.680 500 companies, which transitioned 8 00:00:13.680 --> 00:00:16.940 to a whole line of research that I was able to accomplish, 9 00:00:16.940 --> 00:00:19.020 having access to those companies. 10 00:00:19.020 --> 00:00:23.560 If you're pursuing the EDBA program, which I think is great, 11 00:00:23.560 --> 00:00:26.560 there's a number of things from a practitioner and research 12 00:00:26.560 --> 00:00:29.120 standpoint that you could be asking yourself. 13 00:00:29.120 --> 00:00:32.573 In my world of entrepreneurship and corporate innovation, 14 00:00:32.573 --> 00:00:34.240 obviously, there's a number of questions 15 00:00:34.240 --> 00:00:35.460 that still reside out there. 16 00:00:35.460 --> 00:00:39.320 For example, how will AI change the way corporations 17 00:00:39.320 --> 00:00:41.960 are going to look at innovation inside their companies? 18 00:00:41.960 --> 00:00:44.460 How will it actually maybe drive and enhance it, 19 00:00:44.460 --> 00:00:47.240 or how will it maybe in some ways, 20 00:00:47.240 --> 00:00:49.560 be a hindrance in many ways to the individuals 21 00:00:49.560 --> 00:00:50.938 that want to step forward? 22 00:00:50.938 --> 00:00:52.480 So there's some interesting questions 23 00:00:52.480 --> 00:00:55.422 around the whole AI movement, I think, that is there. 24 00:00:55.422 --> 00:00:56.880 And then when you look at the stuff 25 00:00:56.880 --> 00:00:58.920 that I've been doing in coachability, 26 00:00:58.920 --> 00:01:02.080 and mentors, and accelerators, a lot of questions 27 00:01:02.080 --> 00:01:04.923 arise as to what really is going to be the value? 28 00:01:04.923 --> 00:01:06.840 What is the most important thing that a mentor 29 00:01:06.840 --> 00:01:08.742 can do with an entrepreneur? 30 00:01:08.742 --> 00:01:10.200 And what's the most important thing 31 00:01:10.200 --> 00:01:13.900 entrepreneurs can do to find the proper mentor, the proper match, 32 00:01:13.900 --> 00:01:14.760 if you will? 33 00:01:14.760 --> 00:01:16.960 So a number of questions that I think, 34 00:01:16.960 --> 00:01:20.760 from a practitioner standpoint, can be looked at and applied, 35 00:01:20.760 --> 00:01:23.663 and eventually, through a study, published. 36 00:01:23.663 --> 00:01:25.080 So for all of you, I encourage you 37 00:01:25.080 --> 00:01:26.880 to think about our doctoral programs 38 00:01:26.880 --> 00:01:28.620 here at the Kelley School of Business. 39 00:01:28.620 --> 00:01:31.160 Because as you can see from the research that I'm doing 40 00:01:31.160 --> 00:01:33.180 and research that my colleagues are doing, 41 00:01:33.180 --> 00:01:37.320 we are entering some pretty significant areas of study. 42 00:01:37.320 --> 00:01:38.900 And I think as a doctoral student, 43 00:01:38.900 --> 00:01:41.440 you will find it most interesting, exciting, 44 00:01:41.440 --> 00:01:44.420 and challenging to work with some of our professors. 45 00:01:44.420 --> 00:01:47.580 And I hope in some cases, if you're interested in my world, 46 00:01:47.580 --> 00:01:48.628 you'll work with me. 47 00:01:48.628 --> 00:01:50.420 But it would be great to have you on board. 48 00:01:50.420 --> 00:01:51.360 Thanks so much. 49 00:01:51.360 --> 00:01:54.710 [WHIRRING] 50 00:01:54.710 --> 00:01:57.000

Description of the video:

WEBVTT 1 00:00:00.000 --> 00:00:01.360 2 00:00:01.360 --> 00:00:05.360 My research falls within the broad field 3 00:00:05.360 --> 00:00:08.080 of organizational behavior, and I'm 4 00:00:08.080 --> 00:00:11.600 very interested in leadership and leadership processes. 5 00:00:11.600 --> 00:00:14.780 And under that umbrella of leadership, 6 00:00:14.780 --> 00:00:19.760 I tended to look at ambivalence or cognitive tensions. 7 00:00:19.760 --> 00:00:23.240 Individuals can hold positive and negative evaluations 8 00:00:23.240 --> 00:00:27.920 about a situation, and that creates this cognitive tension. 9 00:00:27.920 --> 00:00:32.080 So I tended to look at how ambivalence influence 10 00:00:32.080 --> 00:00:38.060 leadership processes and how the leader interacts with followers. 11 00:00:38.060 --> 00:00:43.200 When looking at the practical implications of my research, 12 00:00:43.200 --> 00:00:45.460 I tended to focus on behaviors. 13 00:00:45.460 --> 00:00:50.200 So what are the functional and dysfunctional behaviors 14 00:00:50.200 --> 00:00:53.320 that leaders engage in your organization 15 00:00:53.320 --> 00:00:55.120 or in your industry? 16 00:00:55.120 --> 00:00:59.800 And in particular, I'm very interested in those contexts 17 00:00:59.800 --> 00:01:03.280 that are very complex, interdependent, and dynamic 18 00:01:03.280 --> 00:01:04.920 because guess what? 19 00:01:04.920 --> 00:01:08.310 Leaders are important in those situations. 20 00:01:08.310 --> 00:01:11.370 So if we can understand how leaders behave 21 00:01:11.370 --> 00:01:13.050 in those complex, interdependent, 22 00:01:13.050 --> 00:01:18.010 and dynamic situations, we can understand their cognitions 23 00:01:18.010 --> 00:01:18.990 as well. 24 00:01:18.990 --> 00:01:21.470 And the cognitions, in particular ambivalence, 25 00:01:21.470 --> 00:01:25.170 this is one of the cognitions that I'm particularly interested 26 00:01:25.170 --> 00:01:26.250 in. 27 00:01:26.250 --> 00:01:29.250 Ambivalence can predict how leaders 28 00:01:29.250 --> 00:01:34.070 interact, how leaders behave, how they make decisions. 29 00:01:34.070 --> 00:01:38.450 And not only that, in recent projects that I have, 30 00:01:38.450 --> 00:01:42.050 we are looking into followers and how followers 31 00:01:42.050 --> 00:01:46.010 experiencing ambivalence, what happens with them. 32 00:01:46.010 --> 00:01:48.690 Are they promoted? 33 00:01:48.690 --> 00:01:50.830 Are they given new opportunities? 34 00:01:50.830 --> 00:01:55.090 People like working with those ambivalent followers as well? 35 00:01:55.090 --> 00:02:00.370 So to summarize, I look at behaviors of leaders and perhaps 36 00:02:00.370 --> 00:02:04.690 followers as well and how those are functional and dysfunctional 37 00:02:04.690 --> 00:02:07.380 in leadership processes. 38 00:02:07.380 --> 00:02:12.000

Description of the video:

WEBVTT 1 00:00:00.000 --> 00:00:01.640 2 00:00:01.640 --> 00:00:04.360 I am someone who studies organizational behavior 3 00:00:04.360 --> 00:00:07.040 and human resources within organizations. 4 00:00:07.040 --> 00:00:09.280 What that means is that I'm interested in the way 5 00:00:09.280 --> 00:00:11.440 that organizational systems, and more 6 00:00:11.440 --> 00:00:13.920 particularly, organizational leaders, 7 00:00:13.920 --> 00:00:17.180 influence folks who are working for those organizations. 8 00:00:17.180 --> 00:00:20.000 One of the questions that I think EDBA students 9 00:00:20.000 --> 00:00:23.360 might be interested in centers around my beliefs 10 00:00:23.360 --> 00:00:25.080 that negotiation is something that we 11 00:00:25.080 --> 00:00:28.320 do every day in organizations, and that by training 12 00:00:28.320 --> 00:00:32.040 people in negotiations formally, we actually make them 13 00:00:32.040 --> 00:00:34.760 better at informal exchanges. 14 00:00:34.760 --> 00:00:38.360 So as I teach negotiation in the MBA program 15 00:00:38.360 --> 00:00:40.560 and actually have been on negotiation faculty 16 00:00:40.560 --> 00:00:42.760 for more than 30 years, I've watched 17 00:00:42.760 --> 00:00:45.240 the way in which my students change 18 00:00:45.240 --> 00:00:48.180 after they take the class, not just from confidence, 19 00:00:48.180 --> 00:00:50.080 but in the way that they will figure out 20 00:00:50.080 --> 00:00:53.280 what they want to ask for, be more strategic in the things 21 00:00:53.280 --> 00:00:55.280 that they bring to a conversation. 22 00:00:55.280 --> 00:00:57.080 So I really would like to study some 23 00:00:57.080 --> 00:01:00.600 of the impacts of that on someone's day-to-day work life. 24 00:01:00.600 --> 00:01:04.660 Does negotiation training make them more likely to make an ask? 25 00:01:04.660 --> 00:01:09.160 Does it make them more likely to have more prepared commentary 26 00:01:09.160 --> 00:01:11.200 when they go into that situation? 27 00:01:11.200 --> 00:01:13.920 We know that training in negotiation 28 00:01:13.920 --> 00:01:16.520 really eliminates the gender gap. 29 00:01:16.520 --> 00:01:18.840 Women and men trained in negotiation 30 00:01:18.840 --> 00:01:21.780 will ask for salary raises, for example, at equal rates. 31 00:01:21.780 --> 00:01:24.400 I'm intrigued to find out if that training has 32 00:01:24.400 --> 00:01:26.990 other great outcomes as well. 33 00:01:26.990 --> 00:01:31.000

Description of the video:

WEBVTT 1 00:00:00.000 --> 00:00:01.240 2 00:00:01.240 --> 00:00:03.760 My research, really, stems from my background 3 00:00:03.760 --> 00:00:05.840 in industry, which I think is relevant 4 00:00:05.840 --> 00:00:10.000 when we're talking about working with applied, more applied DBA 5 00:00:10.000 --> 00:00:10.880 students. 6 00:00:10.880 --> 00:00:13.560 I worked at Deloitte Consulting for several years 7 00:00:13.560 --> 00:00:15.640 doing strategy consulting, and then 8 00:00:15.640 --> 00:00:19.560 moved into working for our CEO and chief transformation 9 00:00:19.560 --> 00:00:22.480 officer, chief strategy officer. 10 00:00:22.480 --> 00:00:24.840 And while I was there, what I noticed 11 00:00:24.840 --> 00:00:28.240 most was so many of the challenges that arise in running 12 00:00:28.240 --> 00:00:31.520 these huge businesses, like Deloitte or Fortune 500 13 00:00:31.520 --> 00:00:33.680 companies, has to do with people. 14 00:00:33.680 --> 00:00:35.700 And that was what I was most fascinated with. 15 00:00:35.700 --> 00:00:38.240 And so my value for learning and discovery 16 00:00:38.240 --> 00:00:39.660 led me back to academia. 17 00:00:39.660 --> 00:00:42.240 And so it's a joy now to be a professor where 18 00:00:42.240 --> 00:00:45.480 I can teach about topics and research 19 00:00:45.480 --> 00:00:48.080 about topics related to people. 20 00:00:48.080 --> 00:00:53.720 And so when I'm not teaching or running programs and helping out 21 00:00:53.720 --> 00:00:56.280 around the department, around our school, 22 00:00:56.280 --> 00:01:00.520 my research is related to mental health at work, 23 00:01:00.520 --> 00:01:03.730 workers who are more vulnerable maybe 24 00:01:03.730 --> 00:01:07.690 have stigmatized identities like women in business 25 00:01:07.690 --> 00:01:10.570 or for example, a new population of the workforce 26 00:01:10.570 --> 00:01:14.130 called the gig economy, so workers who work off the grid. 27 00:01:14.130 --> 00:01:17.090 I'm sure we can all relate to having to work 28 00:01:17.090 --> 00:01:19.310 in socially remote conditions. 29 00:01:19.310 --> 00:01:23.650 And so those are just a snapshot of the type of research topics 30 00:01:23.650 --> 00:01:26.090 that I work on right now. 31 00:01:26.090 --> 00:01:28.330 Yeah, I think one of the projects that's 32 00:01:28.330 --> 00:01:33.770 most relevant to this group, so I do academic-related projects 33 00:01:33.770 --> 00:01:36.010 that would be published in journals that I 34 00:01:36.010 --> 00:01:39.010 would help you learn to read, if you're interested. 35 00:01:39.010 --> 00:01:41.090 But this particular project that I'm working on 36 00:01:41.090 --> 00:01:45.110 happens to be a student project that is incredibly applied, 37 00:01:45.110 --> 00:01:48.930 and it's actually under revision at a very applied journal, which 38 00:01:48.930 --> 00:01:50.670 means that it's going to get published. 39 00:01:50.670 --> 00:01:55.010 It started as a thesis project, where I had a student come to me 40 00:01:55.010 --> 00:01:58.370 and say that she was incredibly interested in authenticity 41 00:01:58.370 --> 00:02:00.650 at work because what she was finding 42 00:02:00.650 --> 00:02:03.550 is as a woman who veils diligently 43 00:02:03.550 --> 00:02:05.510 for her religious practice, and also 44 00:02:05.510 --> 00:02:09.550 a woman who is highly empowered and working in one 45 00:02:09.550 --> 00:02:12.990 of the biggest, most respected banks in the US, 46 00:02:12.990 --> 00:02:15.370 it was really difficult to balance the two. 47 00:02:15.370 --> 00:02:16.690 And she had a lot of questions. 48 00:02:16.690 --> 00:02:19.230 And so what we did over the course of the year 49 00:02:19.230 --> 00:02:22.430 was conducted interviews in a reasonable way 50 00:02:22.430 --> 00:02:25.470 that she could combine with her extracurriculars and her studies 51 00:02:25.470 --> 00:02:29.530 that helped us arrive at new insights about this question. 52 00:02:29.530 --> 00:02:33.450 And so when I work on highly applied problems, 53 00:02:33.450 --> 00:02:35.150 my goal for working with these students 54 00:02:35.150 --> 00:02:38.870 is to help clarify what the question is, help you understand 55 00:02:38.870 --> 00:02:41.670 what's out there that has already answered 56 00:02:41.670 --> 00:02:44.910 this question so that we can come up with something new 57 00:02:44.910 --> 00:02:45.530 together. 58 00:02:45.530 --> 00:02:48.550 So that is one example. 59 00:02:48.550 --> 00:02:52.290 I'll give you one more example that I'm working on right now. 60 00:02:52.290 --> 00:02:54.010 We actually just put it under review. 61 00:02:54.010 --> 00:02:55.950 It's a project I'm really proud of. 62 00:02:55.950 --> 00:03:00.650 What we did was we looked at workers in the gig economy, 63 00:03:00.650 --> 00:03:04.060 and these happened to be a bunch of freelance journalists. 64 00:03:04.060 --> 00:03:06.800 And one of the things that we noticed from interviews 65 00:03:06.800 --> 00:03:09.960 that we did with these workers, that is a major struggle when 66 00:03:09.960 --> 00:03:14.480 you're alone, sitting in your room trying to be productive 67 00:03:14.480 --> 00:03:16.360 and also feeling well. 68 00:03:16.360 --> 00:03:20.520 And so as professors, I worked with a team of professors 69 00:03:20.520 --> 00:03:21.260 on this. 70 00:03:21.260 --> 00:03:23.680 We said, what if we give this group a tool? 71 00:03:23.680 --> 00:03:26.560 And let's set it up with an experimental paradigm 72 00:03:26.560 --> 00:03:30.640 so that we can start to test a tool that we could go out 73 00:03:30.640 --> 00:03:33.720 to other people in practice, other people in the gig economy 74 00:03:33.720 --> 00:03:35.180 and say, this tool works. 75 00:03:35.180 --> 00:03:40.000 And so what we actually found is that if you as gig workers 76 00:03:40.000 --> 00:03:43.040 or perhaps if you're working socially remote, if you use 77 00:03:43.040 --> 00:03:46.280 something called a Pomodoro technique in a Zoom room 78 00:03:46.280 --> 00:03:49.360 with other people for an hour, you'll actually 79 00:03:49.360 --> 00:03:52.980 get more work done and feel better as a result. 80 00:03:52.980 --> 00:03:57.560 And so these are two examples of projects that are highly applied 81 00:03:57.560 --> 00:04:01.060 and have real novel insights that can really help people. 82 00:04:01.060 --> 00:04:04.410 [DRAMATIC SOUND] 83 00:04:04.410 --> 00:04:06.000

Description of the video:

WEBVTT 1 00:00:00.000 --> 00:00:02.120 2 00:00:02.120 --> 00:00:05.220 So I tend to study what I call funky contacts. 3 00:00:05.220 --> 00:00:08.039 I'm a phenomenologist, so I study 4 00:00:08.039 --> 00:00:09.580 things that just interest me. 5 00:00:09.580 --> 00:00:12.840 And often that comes from just interviewing and interacting 6 00:00:12.840 --> 00:00:14.080 with people. 7 00:00:14.080 --> 00:00:16.560 I've interviewed people as diverse 8 00:00:16.560 --> 00:00:18.620 as street performers in New Orleans. 9 00:00:18.620 --> 00:00:21.840 I have a stream of research on craft breweries. 10 00:00:21.840 --> 00:00:25.200 I've interviewed millionaire and billionaire founders who 11 00:00:25.200 --> 00:00:27.060 have exited their businesses. 12 00:00:27.060 --> 00:00:30.340 And I also have a research project on Amish entrepreneurs. 13 00:00:30.340 --> 00:00:33.700 And so I tend to engage in qualitative methods. 14 00:00:33.700 --> 00:00:36.560 I enjoy getting out and being in communities 15 00:00:36.560 --> 00:00:40.080 and interviewing entrepreneurs. 16 00:00:40.080 --> 00:00:43.600 So studying entrepreneurship, I think a lot of the questions 17 00:00:43.600 --> 00:00:47.600 that I ask are naturally pretty applied. 18 00:00:47.600 --> 00:00:49.760 And a lot of times my research questions that I do 19 00:00:49.760 --> 00:00:52.040 ask come from something that I see out 20 00:00:52.040 --> 00:00:54.320 in the world among entrepreneurs. 21 00:00:54.320 --> 00:00:56.480 But one of the central themes of my research 22 00:00:56.480 --> 00:00:59.520 is often how growth of organizations 23 00:00:59.520 --> 00:01:03.360 changes or challenges organizations. 24 00:01:03.360 --> 00:01:05.400 And one of the things that I see now 25 00:01:05.400 --> 00:01:08.720 is there's always a move when people start new businesses 26 00:01:08.720 --> 00:01:10.840 to reduce friction. 27 00:01:10.840 --> 00:01:13.320 And what I mean by that is, often we think of maybe 28 00:01:13.320 --> 00:01:17.280 you have the Starbucks app, and it's very easy to order online 29 00:01:17.280 --> 00:01:21.520 and to pick up your coffee with very little human interaction. 30 00:01:21.520 --> 00:01:23.800 And so one of the questions I'm interested in 31 00:01:23.800 --> 00:01:27.840 is oftentimes as we move and we encourage entrepreneurs 32 00:01:27.840 --> 00:01:31.520 to engage in frictionless payments, 33 00:01:31.520 --> 00:01:34.440 or frictionless operations, their operations 34 00:01:34.440 --> 00:01:36.420 become a bit more transactional. 35 00:01:36.420 --> 00:01:40.080 And so my question, I would say from an applied nature 36 00:01:40.080 --> 00:01:42.980 is, even though we want to encourage this, 37 00:01:42.980 --> 00:01:45.160 how do we make this a bit more relational 38 00:01:45.160 --> 00:01:48.400 and encourage relationships and building 39 00:01:48.400 --> 00:01:50.220 relationships with your customers, 40 00:01:50.220 --> 00:01:53.400 while at the same time reducing the frictions that 41 00:01:53.400 --> 00:01:56.320 often occur when you're interacting with customers? 42 00:01:56.320 --> 00:01:59.670 [WHIRRING] 43 00:01:59.670 --> 00:02:02.000

Description of the video:

WEBVTT 1 00:00:00.000 --> 00:00:01.560 2 00:00:01.560 --> 00:00:04.820 My research interests focus in three primary areas, 3 00:00:04.820 --> 00:00:07.960 so I look at emotions and affect in the workplace, things 4 00:00:07.960 --> 00:00:10.580 like emotional regulation and emotional labor. 5 00:00:10.580 --> 00:00:12.600 So when we'd have to fake or modify 6 00:00:12.600 --> 00:00:15.900 our emotions to meet display demands in our environment. 7 00:00:15.900 --> 00:00:18.860 I also look at justice in the workplace. 8 00:00:18.860 --> 00:00:22.000 So how we feel about our boss, perceptions, and behaviors, 9 00:00:22.000 --> 00:00:25.140 and how that might affect how we actually engage and work. 10 00:00:25.140 --> 00:00:27.740 And then I also look at decision making biases. 11 00:00:27.740 --> 00:00:29.680 So biases like escalation of commitment 12 00:00:29.680 --> 00:00:32.123 when we might continue with a failing course of action 13 00:00:32.123 --> 00:00:34.040 because it's really tied to our identity or we 14 00:00:34.040 --> 00:00:36.240 spend a lot of time working on it already. 15 00:00:36.240 --> 00:00:39.080 So talking about malicious compliance or situations 16 00:00:39.080 --> 00:00:42.980 where someone might follow the letter of the law, 17 00:00:42.980 --> 00:00:45.880 but not the spirit of the law or situations 18 00:00:45.880 --> 00:00:48.840 where someone might see a sign, driving by and says, 19 00:00:48.840 --> 00:00:52.240 my boss told me to change this sign and so I did. 20 00:00:52.240 --> 00:00:55.200 Where you're violating the spirit of what someone 21 00:00:55.200 --> 00:00:57.740 wanted, but you're kind of trying to prove a point. 22 00:00:57.740 --> 00:01:00.280 Something an EDBA student could look at here 23 00:01:00.280 --> 00:01:04.060 was how malicious compliance plays out in different contexts. 24 00:01:04.060 --> 00:01:06.080 So what would this look like in healthcare 25 00:01:06.080 --> 00:01:07.680 when nurses are doing what they're 26 00:01:07.680 --> 00:01:11.900 told but it's not really the right way of doing things. 27 00:01:11.900 --> 00:01:14.380 And they know it's going to have an unintended bad outcome 28 00:01:14.380 --> 00:01:16.620 but they do it anyway to prove a point, 29 00:01:16.620 --> 00:01:18.720 or how would that look different in manufacturing 30 00:01:18.720 --> 00:01:20.360 or in a different industry. 31 00:01:20.360 --> 00:01:23.440 Or there could be contacts where an individual has 32 00:01:23.440 --> 00:01:27.300 a lot more flexibility of how they can even bend the rules. 33 00:01:27.300 --> 00:01:30.280 And so this is an example of how we could look at this further 34 00:01:30.280 --> 00:01:32.100 with an EDBA student. 35 00:01:32.100 --> 00:01:35.150 [AUDIO LOGO] 36 00:01:35.150 --> 00:01:38.000

Description of the video:

WEBVTT 1 00:00:00.000 --> 00:00:04.320 WILL GEOGHEGAN: My research interests predominantly align 2 00:00:04.320 --> 00:00:05.920 to two main areas. 3 00:00:05.920 --> 00:00:09.320 The more traditional strategy research, and as such, 4 00:00:09.320 --> 00:00:12.200 I've done a lot of work on strategic management, 5 00:00:12.200 --> 00:00:15.960 on innovative capabilities, and on technology transfer, 6 00:00:15.960 --> 00:00:19.880 specifically technology transfer from universities 7 00:00:19.880 --> 00:00:22.160 to firms in industry. 8 00:00:22.160 --> 00:00:25.420 The second major research theme, or strand, 9 00:00:25.420 --> 00:00:28.220 is one that I've jumped into more recently, 10 00:00:28.220 --> 00:00:31.000 and that's one on technology and innovation. 11 00:00:31.000 --> 00:00:33.400 So specifically, business education, 12 00:00:33.400 --> 00:00:36.500 the evolution of online business education, 13 00:00:36.500 --> 00:00:40.560 including student engagement and program differentiation. 14 00:00:40.560 --> 00:00:44.920 I've also really enjoyed looking into technological innovation 15 00:00:44.920 --> 00:00:48.320 in education more recently as a driver for more 16 00:00:48.320 --> 00:00:51.160 effective business education. 17 00:00:51.160 --> 00:00:55.240 Topics such as generative AI, virtual reality, 18 00:00:55.240 --> 00:00:58.040 all of those emerging technologies 19 00:00:58.040 --> 00:01:02.160 that are super interesting to understand in a business 20 00:01:02.160 --> 00:01:03.160 context. 21 00:01:03.160 --> 00:01:05.920 Anything in the realm of innovation and capabilities 22 00:01:05.920 --> 00:01:07.680 would be of interest to me. 23 00:01:07.680 --> 00:01:11.520 How effectively does a firm build, acquire, or integrate 24 00:01:11.520 --> 00:01:13.800 new capabilities, whether that's with partnering 25 00:01:13.800 --> 00:01:16.040 with universities or suppliers? 26 00:01:16.040 --> 00:01:18.480 Questions with regard to strategic positioning 27 00:01:18.480 --> 00:01:20.320 and competitive advantage. 28 00:01:20.320 --> 00:01:22.600 How does your firm's value proposition 29 00:01:22.600 --> 00:01:24.420 compare to key competitors? 30 00:01:24.420 --> 00:01:29.240 And what strategic capabilities differentiate you in practice? 31 00:01:29.240 --> 00:01:32.480 And then the ones that I've developed more recently 32 00:01:32.480 --> 00:01:36.120 with regard to technology, the future of work and business 33 00:01:36.120 --> 00:01:37.100 education. 34 00:01:37.100 --> 00:01:40.000 How is your company leveraging emerging technologies 35 00:01:40.000 --> 00:01:42.640 in support of leadership development, learning, 36 00:01:42.640 --> 00:01:44.200 or talent pipeline? 37 00:01:44.200 --> 00:01:47.720 What practices most effectively enhance engagement 38 00:01:47.720 --> 00:01:51.320 and performance in hybrid or online professional development 39 00:01:51.320 --> 00:01:52.840 programs? 40 00:01:52.840 --> 00:01:55.520 Generative AI questions abound. 41 00:01:55.520 --> 00:02:00.000 What generative AI practices are most effective in business 42 00:02:00.000 --> 00:02:00.940 education? 43 00:02:00.940 --> 00:02:03.560 What are the barriers or bottlenecks? 44 00:02:03.560 --> 00:02:05.900 What instructional technological tools, 45 00:02:05.900 --> 00:02:10.100 whether that's AI tools, virtual whiteboard tools, simulations, 46 00:02:10.100 --> 00:02:12.920 or interactive tools, actually improve 47 00:02:12.920 --> 00:02:14.800 learner engagement and performance 48 00:02:14.800 --> 00:02:17.520 in hybrid or online courses? 49 00:02:17.520 --> 00:02:20.140 How do different modes of case teaching, 50 00:02:20.140 --> 00:02:23.300 whether it's asynchronous, synchronous, or blended, 51 00:02:23.300 --> 00:02:26.600 affect critical thinking and strategic decision-making 52 00:02:26.600 --> 00:02:27.680 outcomes? 53 00:02:27.680 --> 00:02:31.020 Which program innovations, immersive experiences, 54 00:02:31.020 --> 00:02:33.560 global projects, industry partnerships, 55 00:02:33.560 --> 00:02:37.680 create the highest perceived value for online MBA students? 56 00:02:37.680 --> 00:02:42.080 And I can go on and on and on, but a limited amount of time, 57 00:02:42.080 --> 00:02:47.320 there is a myriad of different possible application questions 58 00:02:47.320 --> 00:02:51.120 that would be hugely interesting for you, either in the strategy 59 00:02:51.120 --> 00:02:54.550 realm or in the education realm. 60 00:02:54.550 --> 00:02:58.000

Description of the video:

WEBVTT 1 00:00:00.000 --> 00:00:00.660 2 00:00:00.660 --> 00:00:01.660 TOMASZ OBLOJ: All right. 3 00:00:01.660 --> 00:00:03.680 So I think that research interests are probably 4 00:00:03.680 --> 00:00:05.780 best described with examples. 5 00:00:05.780 --> 00:00:08.760 So let me just give you quick examples of the three most 6 00:00:08.760 --> 00:00:11.920 recent projects that I've been working on that ended up being 7 00:00:11.920 --> 00:00:14.200 published in academic journals. 8 00:00:14.200 --> 00:00:18.000 So the first project was actually a multi-paper project 9 00:00:18.000 --> 00:00:22.000 that looked at the consequences of pay transparency. 10 00:00:22.000 --> 00:00:24.060 And along with a team of co-authors, 11 00:00:24.060 --> 00:00:25.960 we looked at different consequences 12 00:00:25.960 --> 00:00:27.720 of pay transparency. 13 00:00:27.720 --> 00:00:30.340 The first one was gender pay equity, 14 00:00:30.340 --> 00:00:32.800 and the second one was productivity. 15 00:00:32.800 --> 00:00:35.020 And looking at the effects of pay transparency, 16 00:00:35.020 --> 00:00:38.020 we actually uncovered a bunch of really interesting mechanisms, 17 00:00:38.020 --> 00:00:39.140 at least I think so. 18 00:00:39.140 --> 00:00:42.560 So first, pay transparency in organizations 19 00:00:42.560 --> 00:00:47.220 leads to decreased inequity in wages. 20 00:00:47.220 --> 00:00:48.360 So this is great. 21 00:00:48.360 --> 00:00:50.700 Now, the side effect of wage transparency, 22 00:00:50.700 --> 00:00:55.180 however, was that the power of incentives was also muted. 23 00:00:55.180 --> 00:00:58.300 So people were paid more equitably, 24 00:00:58.300 --> 00:01:00.680 but they were also paid more similarly 25 00:01:00.680 --> 00:01:04.480 even across different performance levels. 26 00:01:04.480 --> 00:01:06.350 Then we kind of dived a little bit deeper 27 00:01:06.350 --> 00:01:10.870 and we started looking at productivity consequences of pay 28 00:01:10.870 --> 00:01:11.890 transparency. 29 00:01:11.890 --> 00:01:14.430 And what we discovered is that people 30 00:01:14.430 --> 00:01:17.270 who discovered through pay transparency 31 00:01:17.270 --> 00:01:20.630 that they were overpaid, inequitably overpaid, 32 00:01:20.630 --> 00:01:23.510 started putting in more effort, potentially 33 00:01:23.510 --> 00:01:26.750 to justify their high wages to their peers. 34 00:01:26.750 --> 00:01:28.750 On the flip side, people who discovered 35 00:01:28.750 --> 00:01:31.430 they're inequitably underpaid started 36 00:01:31.430 --> 00:01:36.490 putting in less effort to align their inputs with the rewards. 37 00:01:36.490 --> 00:01:39.550 Overall, we found a slightly positive effect 38 00:01:39.550 --> 00:01:41.690 of pay transparency on productivity, 39 00:01:41.690 --> 00:01:43.670 but what we pretty much were interested in 40 00:01:43.670 --> 00:01:47.910 was uncovering or unmasking this heterogeneous responses. 41 00:01:47.910 --> 00:01:48.410 All right. 42 00:01:48.410 --> 00:01:50.210 So this was the first research project. 43 00:01:50.210 --> 00:01:53.890 The second research project, which may seem very dissimilar, 44 00:01:53.890 --> 00:01:55.930 is actually similar on some dimensions, 45 00:01:55.930 --> 00:01:58.710 and I'll come to that in a second. 46 00:01:58.710 --> 00:02:02.430 So there's a notion that firm-specific human capital 47 00:02:02.430 --> 00:02:04.490 is very beneficial to organizations. 48 00:02:04.490 --> 00:02:06.350 So this is the type of human capital 49 00:02:06.350 --> 00:02:10.470 that is most productive when used in the focal organization 50 00:02:10.470 --> 00:02:13.990 and less productive when applied in competitors 51 00:02:13.990 --> 00:02:16.170 or in other organizations. 52 00:02:16.170 --> 00:02:18.830 So firms want their employees to have a lot 53 00:02:18.830 --> 00:02:20.990 of firm-specific human capital. 54 00:02:20.990 --> 00:02:24.250 A, because that makes those employees more productive, 55 00:02:24.250 --> 00:02:26.230 but also because these employees are 56 00:02:26.230 --> 00:02:28.270 less likely to leave because they have 57 00:02:28.270 --> 00:02:31.430 a bunch of human capital that's most valuable 58 00:02:31.430 --> 00:02:33.830 within the organization. 59 00:02:33.830 --> 00:02:36.230 So again, looking at a very detailed data 60 00:02:36.230 --> 00:02:39.750 in the retail banking setting, what I looked at 61 00:02:39.750 --> 00:02:41.830 and what I focused on was the dark side 62 00:02:41.830 --> 00:02:43.830 of firm-specific human capital. 63 00:02:43.830 --> 00:02:46.110 And I uncovered that those employees that 64 00:02:46.110 --> 00:02:48.510 are most productive through their firm-specific human 65 00:02:48.510 --> 00:02:52.990 capital, they are also best at extracting value 66 00:02:52.990 --> 00:02:54.352 through incentive gaming. 67 00:02:54.352 --> 00:02:56.310 So there is some balance, and this is something 68 00:02:56.310 --> 00:02:58.150 that I really like in research. 69 00:02:58.150 --> 00:03:00.850 Now, what links together these two projects, 70 00:03:00.850 --> 00:03:05.750 even though they may seem very distant is that, 71 00:03:05.750 --> 00:03:07.830 and this is what I study in my research overall, 72 00:03:07.830 --> 00:03:09.990 is that I link organizational design 73 00:03:09.990 --> 00:03:13.030 choices, behavioral micro-level mechanisms 74 00:03:13.030 --> 00:03:14.700 at the individual level, and then 75 00:03:14.700 --> 00:03:16.880 a range of outcomes for organizations. 76 00:03:16.880 --> 00:03:19.200 And those outcomes can be financial performance. 77 00:03:19.200 --> 00:03:22.500 They can be societal performance, so different 78 00:03:22.500 --> 00:03:23.940 objective function. 79 00:03:23.940 --> 00:03:25.860 They can be mobility. 80 00:03:25.860 --> 00:03:27.740 They can be competitive outcomes, so 81 00:03:27.740 --> 00:03:28.660 a range of outcomes. 82 00:03:28.660 --> 00:03:31.840 I'm really fairly agnostic to which outcome I study. 83 00:03:31.840 --> 00:03:35.420 I'm much more interested in the micro-level mechanisms 84 00:03:35.420 --> 00:03:37.820 that lead organizations to perform better 85 00:03:37.820 --> 00:03:40.580 or worse on some dimension. 86 00:03:40.580 --> 00:03:44.180 So if I'm going to be working with EDBA students, 87 00:03:44.180 --> 00:03:46.560 I would like them to get their hands dirty. 88 00:03:46.560 --> 00:03:49.420 I would like to get their hands dirty with data, 89 00:03:49.420 --> 00:03:54.160 with actual organizational decisions, with design choices 90 00:03:54.160 --> 00:03:58.340 under an overarching umbrella of linking organization design 91 00:03:58.340 --> 00:04:00.640 choices-- this could be transparency, 92 00:04:00.640 --> 00:04:04.160 it could be incentive systems, it could be ownership structure, 93 00:04:04.160 --> 00:04:06.140 it could be the level of autonomy, 94 00:04:06.140 --> 00:04:08.800 any design, structural design choice, 95 00:04:08.800 --> 00:04:11.700 and linking that to a range of objectives 96 00:04:11.700 --> 00:04:12.760 that firms may pursue. 97 00:04:12.760 --> 00:04:14.680 Some firms pursue multiple objectives. 98 00:04:14.680 --> 00:04:18.260 Some firms pursue only one objective, though very few, 99 00:04:18.260 --> 00:04:21.700 but really trying to understand those linkages. 100 00:04:21.700 --> 00:04:25.580 I work with a range of methods, from lab experiments 101 00:04:25.580 --> 00:04:28.300 to field experiments, A/B testing, 102 00:04:28.300 --> 00:04:31.900 analyzing large archival data, but also 103 00:04:31.900 --> 00:04:34.540 looking at surveys or questionnaires 104 00:04:34.540 --> 00:04:36.220 within an organization. 105 00:04:36.220 --> 00:04:39.340 I would love to work with EDBA students 106 00:04:39.340 --> 00:04:42.140 on data from the organizations, if they're 107 00:04:42.140 --> 00:04:45.320 able to get this data in which they currently work. 108 00:04:45.320 --> 00:04:49.780 But I'm also very happy to share different data sets that I have, 109 00:04:49.780 --> 00:04:54.700 or we can collectively collect publicly available data 110 00:04:54.700 --> 00:04:58.220 to study these relationships in depth. 111 00:04:58.220 --> 00:05:04.340 Again, all around three somewhat interconnected elements, 112 00:05:04.340 --> 00:05:07.760 individual level, micro processes. 113 00:05:07.760 --> 00:05:09.620 It could be cognitive biases, could be 114 00:05:09.620 --> 00:05:12.280 decision-making patterns or structures, 115 00:05:12.280 --> 00:05:14.340 organization design choices. 116 00:05:14.340 --> 00:05:16.360 And then finally, at the most macro level, 117 00:05:16.360 --> 00:05:18.570 organizational outcomes. 118 00:05:18.570 --> 00:05:23.000

Description of the video:

WEBVTT 1 00:00:00.000 --> 00:00:01.280 2 00:00:01.280 --> 00:00:02.780 ERNEST O'BOYLE: So broadly speaking, 3 00:00:02.780 --> 00:00:05.160 my research falls into two large buckets. 4 00:00:05.160 --> 00:00:07.500 The first is going to be methods and statistics. 5 00:00:07.500 --> 00:00:11.660 So it's meta analysis, systematic review, 6 00:00:11.660 --> 00:00:14.000 structural equation modeling, multiverse analysis, 7 00:00:14.000 --> 00:00:15.520 all very exciting stuff. 8 00:00:15.520 --> 00:00:19.040 And then my second bucket, though, which is substantive, 9 00:00:19.040 --> 00:00:23.680 I look at things that fall within the Organizational 10 00:00:23.680 --> 00:00:27.520 Behavior Human Resources domain, OBHR. 11 00:00:27.520 --> 00:00:29.580 Whereas a lot of the research is in my field, 12 00:00:29.580 --> 00:00:31.663 we're always trying to look at what are the things 13 00:00:31.663 --> 00:00:33.940 that increase performance, increase team productivity, 14 00:00:33.940 --> 00:00:37.020 increase organizational outcomes, and all that stuff, 15 00:00:37.020 --> 00:00:38.320 I look at the opposite end. 16 00:00:38.320 --> 00:00:40.320 What are the things that get in the way of that? 17 00:00:40.320 --> 00:00:42.760 What are the types of predictors of things 18 00:00:42.760 --> 00:00:44.700 like counterproductive work behaviors, 19 00:00:44.700 --> 00:00:47.740 workplace deviance, employee theft, organizational fraud, 20 00:00:47.740 --> 00:00:50.900 quid pro quo sexual harassment, dysfunctional team dynamics, 21 00:00:50.900 --> 00:00:53.660 organizational malfeasance, fraud. 22 00:00:53.660 --> 00:00:57.000 All that bad stuff, I look for the predictors of that. 23 00:00:57.000 --> 00:01:01.860 So in one sense, I am looking at, for lack of a better term, 24 00:01:01.860 --> 00:01:02.600 evil. 25 00:01:02.600 --> 00:01:06.320 But I'm always looking at it not so much through a bad apple 26 00:01:06.320 --> 00:01:08.300 lens, but through a bad barrel lens. 27 00:01:08.300 --> 00:01:09.940 What are the types of policies? 28 00:01:09.940 --> 00:01:12.300 What are the types of selection procedures 29 00:01:12.300 --> 00:01:15.700 that tend to get organizations what they don't want? 30 00:01:15.700 --> 00:01:21.940 An EDBA has a lot going for them that a traditional PhD student 31 00:01:21.940 --> 00:01:22.820 doesn't. 32 00:01:22.820 --> 00:01:25.900 And where I would probably put it, 33 00:01:25.900 --> 00:01:31.140 most notably, is in access and experience 34 00:01:31.140 --> 00:01:35.540 that EDBAs have that oftentimes our traditional PhD students 35 00:01:35.540 --> 00:01:36.500 lack. 36 00:01:36.500 --> 00:01:40.340 So what I think of an EDBA, an ideal project, 37 00:01:40.340 --> 00:01:42.900 when they're putting together their magnum opus, 38 00:01:42.900 --> 00:01:44.980 I can look at them bringing to bear evidence 39 00:01:44.980 --> 00:01:46.560 from one of two sources. 40 00:01:46.560 --> 00:01:49.037 They can either go external, in which case 41 00:01:49.037 --> 00:01:51.120 they're going to conduct like a systematic review. 42 00:01:51.120 --> 00:01:54.500 They're going to go out and find all the extant evidence on work 43 00:01:54.500 --> 00:01:57.420 from home, or results-only work environments, 44 00:01:57.420 --> 00:02:00.260 or team-based incentives or whatever it may be. 45 00:02:00.260 --> 00:02:03.020 And they're going to meta analyze that or review 46 00:02:03.020 --> 00:02:04.000 that full literature. 47 00:02:04.000 --> 00:02:04.760 And that's great. 48 00:02:04.760 --> 00:02:06.140 And that's one path. 49 00:02:06.140 --> 00:02:07.920 The one that I'm really excited about 50 00:02:07.920 --> 00:02:11.020 and what makes me just especially 51 00:02:11.020 --> 00:02:14.100 eager to teach in the EDBA program 52 00:02:14.100 --> 00:02:18.440 are internally-sourced data, internally-sourced evidence, 53 00:02:18.440 --> 00:02:19.460 if you will. 54 00:02:19.460 --> 00:02:22.560 Meaning, you're going to be able to run an experiment 55 00:02:22.560 --> 00:02:24.400 within your organization. 56 00:02:24.400 --> 00:02:27.280 You're going to be able to test out whether or not 57 00:02:27.280 --> 00:02:29.720 this new group decision-making policy, 58 00:02:29.720 --> 00:02:32.680 or procedure, or tactic results in better 59 00:02:32.680 --> 00:02:35.080 outcomes than the old one does. 60 00:02:35.080 --> 00:02:37.860 You're going to be able to learn, OK, this is yes, 61 00:02:37.860 --> 00:02:39.800 a lot of-- we give away a ton of surveys 62 00:02:39.800 --> 00:02:41.660 and anybody can design a survey. 63 00:02:41.660 --> 00:02:44.160 Relatively few can design a good one. 64 00:02:44.160 --> 00:02:46.480 And we'll teach you, what are the tricks, what 65 00:02:46.480 --> 00:02:49.120 are the tactics, what are the ways that question 66 00:02:49.120 --> 00:02:50.540 orders matters? 67 00:02:50.540 --> 00:02:54.240 What are the ways that you want to ask a question to make 68 00:02:54.240 --> 00:02:56.680 sure that you're getting at what the truth of it 69 00:02:56.680 --> 00:03:00.400 is versus what this person wants you to think they are doing 70 00:03:00.400 --> 00:03:03.400 in their organization or on their team 71 00:03:03.400 --> 00:03:06.080 or in their individual contributions? 72 00:03:06.080 --> 00:03:08.040 So to me, I look at that as really 73 00:03:08.040 --> 00:03:13.120 an outstanding opportunity for a experienced professional that 74 00:03:13.120 --> 00:03:15.440 wants to get serious about evidence 75 00:03:15.440 --> 00:03:18.440 and wants to get serious about applying management 76 00:03:18.440 --> 00:03:20.480 theory, and management methodology, 77 00:03:20.480 --> 00:03:25.630 and management research to their day-to-day management. 78 00:03:25.630 --> 00:03:31.000